UNIVERSIDADE TÉCNICA DE LISBOA FACULDADE DE ARQUITECTURA
Building a Pre-Design Ontology Towards a model for urban programs
Nuno Filipe Santos de Castro Montenegro (Licenciado)
DISSERTAÇÃO PARA OBTENÇÃO DO GRAU DE MESTRE EM REGENERAÇÃO URBANA E AMBIENTAL
Orientador Científico: Doutor José Manuel Pinto Duarte Co-orientador Científico: Doutor George Stiny Jurí: Presidente: Doutor Luís António dos Santos Romão Vogais: Doutor João Altino Serra de Magalhães Doutor José Manuel Pinto Duarte Doutor George Stiny Lisboa, Junho de 2010
building a pre-design ontology: towards a model for urban programs
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building a pre-design ontology: towards a model for urban programs
Nuno Filipe Santos de Castro Montenegro Departamento: Urbanismo Orientador Científico: Professor Doutor José Manuel Pinto Duarte Data: Junho de 2010
TÍTULO 1
Uma Ontologia para Planeamento : Contributo para um modelo de programas urbanos
RESUMO O objectivo deste estudo é a formulação de soluções para problemas urbanos. O estudo parte da teoria da linguagem padrão de Christopher Alexander e de um conjunto de informações relativas a regulamentos e recomendações aplicáveis ao planeamento urbano, para elaborar um sistema que gera as especificações ou os ingredientes de um plano; dada uma escala, um local e uma comunidade específicos. O sistema apoia-se num conjunto de dados necessários ao plano, designadamente estratégias, regulamentos, características físicas do local e socioeconómicas da população. O sistema inclui a classificação e a organização desses dados através de uma sequência de eventos, fases, categorias, métodos e utilizadores. O objectivo é descrever os níveis taxonómicos do sistema e as relações de interdependência entre as entidades que compõem o referido sistema. Essa ontologia permitirá fornecer, em investigações futuras, uma estrutura pré-codificada para viabilizar a sua aplicação num modelo computacional, apoiada no modelo espacial SIG (Sistema de Informação Geográfica). O modelo de formulação urbana é essencialmente concebido para incrementar índices de qualidade, reduzindo ambiguidades, e permitindo administrar o planeamento urbano através de um processo mais flexível e automático.
Palavras-chave: Planeamento urbano, Ontologias, Linguagem Padrão.
1. Planeamento no contexto desta investigação está relacionado com a ferramenta administrativa que normalmente ocorre numa fase anterior ou simultânea ao desenvolvimento do desenho de um plano urbano, permitindo a interpretação de uma dada realidade urbana existente ou desejada, de forma a avalia-la e a estruturar percursos adequados para a implementação. Trata-se de um processo de deliberação que escolhe e organiza acções, antecipando resultados esperados. De acordo com o conceito defendido por Peter Drucker (2007) existem dois critérios indispensáveis ao planeamento: eficácia e eficiência. A eficácia é o critério mais importante, já que nenhum nível de eficiência, por mais alto que seja, compensa a má escolha dos objectivos do planeamento, isto é, a eficiência no desempenho das actividades de implementação de um plano sobrepõe-se a eventuais falhas na definição dos objectivos da sua organização.
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building a pre-design ontology: towards a model for urban programs
Nuno Filipe Santos de Castro Montenegro Department: Urbanism Supervisor: Professor Doutor JosĂŠ Manuel Pinto Duarte Date: June 2009
TITLE Building a Pre-Design Ontology: Towards a model for urban programs
ABSTRACT This study is concerned with the formulation of solutions for urban problems. It departs from Alexander’s pattern language theory and from a series of urban design guidelines, to create a system for generating specifications or the ingredients of a plan, given a scale, a site and a community. It takes into account strategies, regulations, guidelines, physical features of the site, and furthermore, the social, cultural and economic characteristics of the population. This system, organised according to a sequence of events, through stages, categories, methods and agents, describes taxonomic levels and their inner relations. Such ontology will provide, in future research, a pattern encoding structure towards a computational model within the capabilities provided by the spatial data modelling of GIS (Geographic Information System). The urban formulation model is conceived to increase qualitative inputs, reducing ambiguities, through a flexible while automated process applied to urban planning.
Keywords: Urban Planning, Ontology, Pattern Language.
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The author owns any copyright© in this thesis and has given the “Technical University of Lisbon, TULisbon” the right to use such Copyright for any administrative, promotional, educational and/or teaching purposes. Copies of this thesis, either in full or in extracts, may be made only in accordance with the regulation of the Faculty of Architecture (FAUTL). The ownership of any patents, designs, trademarks and any and all other intellectua l property rights except for the Copyright (the “Intellectual Property Rights”) and any reproductions of copyright works, for example graphs and tables (“Reproductions”), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual Property Rights and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the relevant Intellectual Property Rights and/or Reproductions.
Cover figure: Pre-design ontological classes and slots sketched in the VizTab of the Protégé 2000 editor.
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1.1.
Contents 1.1.
Contents
1.2.
List of diagrams
1.3.
List of tables and figures
ix
1.4.
Acknowledgements
x
1.5.
Preface
xii
Chapter 1
14
Introduction
vi viii
14
1
1.6.
Introduction
1
1.7.
Research context
1
1.8.
Problem Definition
2
1.9.
Proposed methodology
4
1.10. Concerns involving the creation of the formulation model
6
1.11. Expected outcomes and future work
8
1.12. Organization
10
Chapter 2 Precedents
14
2.1
Introduction
15
2.2
The precedents
15
2.3
Conclusion
20
Chapter 3
23
Methodology
23
3.1.
Introduction
24
3.2.
Adopted methodology
24
3.3.
Ontologies within computer science - (AI) Artificial Intelligence
26
3.4.
Ontology Interoperability
27
3.5.
Representation of ontologies
27
3.6.
Editing ontologies
29
3.7
Comparing ontology editors: Ontolingua and ProtĂŠgĂŠ
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Chapter 4
36
Conceptual and Formulation Models
36
4.1.
Introduction
37
4.2.
The conceptual model
37
4.3.
The formulation model
40
Chapter 5
49
The Formulation Process
49
5.1.
Introduction
50
5.2.
Operational structure of the formulation process
50
5.3.
The formulation phases
52
5.4.
Categories enclosing the main processes of the pre-design phase
53
5.5.
Strategies
54
5.6.
Regulations
59
5.7.
Site and population context
62
5.8.
Document synthesis
70
5.9.
Planner’s Language – pattern language
71
Chapter 6
75
The Sketch of a Planning Language
75
6.1.
Introduction
76
6.2.
The nature of language
76
6.3.
Semantics and Syntax
77
6.4.
Planners and Language processing
80
6.5.
Lexicon
82
6.6.
Pattern Language
84
6.7.
Urban Pattern Language Sketch (UPL)
93
6.8.
The UPL Ontology
93
6.9.
The UPL Syntax and Core Components
94
6.10. The UPL lexicon
100
6.11. The UPL Semantics
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6.12. Conclusion
112
Chapter 7
114
Conclusion
114
7.1 The Context 7.2 The Problem 7.3 The goal 7.4 The model 7.5 The outcome 7.6 Reflexions for future research 7.7 The opportunity
1.2.
Glossary
120
References
134
Annexes
145
List of diagrams 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19.
Basic process of interaction among the three partial modules of the CI project .......................... 1 Change of planning paradigms along time ................................................................................. 3 The core matters of the research............................................................................................... 4 Basic diagram: conceptual outline ............................................................................................. 6 Formulation research outline……………………………………………………………………..………….. ................. 10 Basic diagram: conceptual outline ........................................................................................... 13 The core matters of the research (2)........................................................................................ 13 The main laws of urban programs............................................................................................ 22 Example of an urban pattern top level ontology (see Pinho & Goltz)......................................... 29 Protégé edition of a climatic pattern........................................................................................ 31 The visualization tab of the cold region edited by the Protégé editor ........................................ 31 Ontological class hierarchy of the climatic patterns .................................................................. 32 Methodology framework…………………….. .................................................................................. 35 Duarte’s model (discursive grammar for housing) (Duarte 2007) (Stiny 1981), (Pedro 2001a) and (Stiny & Gips 1972)………………. .......................................................................................... 38 The conceptual model of the urban formulation process (FMo)................................................ 38 The urban formulation ontology (Montenegro, N. and Duarte, J, 2008) .................................... 44 PD classes, subclass-superclass hierarchy, slots and instances, and the Protégé VizTab ............. 47 Urban formulation process (FMo) ............................................................................................ 48 A planning schedule………………….. ............................................................................................ 51
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20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31.
Pre-design phases – the PD1 (data acquisition) and the PD2 (data translation) ......................... 53 The four categories of the formulation process ........................................................................ 54 SWOT analysis - the strengths, the weaknesses, the opportunities, and the threats. ................. 57 Strategies shown in the simplified diagram . ............................................................................ 59 Regulations and codes shown in the simplified diagram . ......................................................... 61 Site and population contextual data shown in the simplified diagram . ..................................... 70 Pattern language “specifications for design” shown in the simplified diagram .......................... 73 The four different categories of the formulation process. ......................................................... 74 Language processing………………….. ........................................................................................... 79 The ontological diagram of an urban pattern (Montenegro, N.C. and Duarte, J.P., 2008) ........... 83 An example of Pattern’s taxonomy (the created links between patterns).................................. 88 Syntax class hierarchical tree (above left), exported piece of XML Schema, CPL diagram classes, subclass-superclass hierarchy, and slots, CPL diagram zoom ........................................ 99 32. UML diagram of the top level class hierarchy (CityGML) ......................................................... 103 33. The core structure of the CPL………… ...................................................................................... 113 34. Syntax class hierarchical tree, exported piece of XML Schema, CPL diagram classes, subclasssuperclass hierarchy, and slots, CPL diagram zoom (2). .......................................................... 160
1.3.
List of tables and figures 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 13.
Benefits of design regulations (Evans et al. 2007) ..................................................................... 60 Gate Counter Map and Observation sheet example (Space Syntax). ......................................... 68 Participants in the planning process (Evans et al. 2007) – part 1 ............................................... 72 Participants in the planning process (Evans et al. 2007) – part 2 ............................................... 72 Active drawing phase during the design (Lindekens 2004) ........................................................ 81 An example of a CityGML code list for city objects (City GML) ................................................ 103 Table with Guterres social patterns (Guterres 2004). ............................................................. 106 Form and proportions of buildings in different regions (Olgyay 1963) ..................................... 108 Design rule formalization on Protégé Axiom Language (Trento 2009) ..................................... 146 Class edition on Protégé 2000………………………………………………………………..……………………………….147 PEST analysis (Chapman 2005)………. ...................................................................................... 154 Attributes applicable to urban formulation (Gil et al 2009) .................................................... 159
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1.4.
Acknowledgements The author would like to express particular gratitude to José P. Duarte, supervisor of this dissertation, for the interest, accuracy, and furthermore a high regard for his scientific depth of outstanding relevance. The author is also thankful to the City Induction project team members, José N. Beirão (TULisbon2/TUDelft3) and Jorge Gil (SpaceSyntax4/TUDelft), through the City Induction project 5 (PTDC/AUR/64384/2006), for the engaging discussions and valuable comments during the development of the research.
I dedicate this thesis in memory of my father
2. http://www.moveonnet.eu/directory/institution?id=PTLISBOA04 3 . http://www.tudelft.nl/ 4 . http://www.spacesyntax.com/
5 . The ICIST (FCT).
project PTDC/AUR/64384/2006 was funded by Fundação para a Ciência e Tecnologia and hosted by
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Good planning is good urban design (Evans et al. 2007)
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1.5.
Preface When, in 2006, Jorge Rocha 6 encouraged me to submit a research project on ontologies7 for funding purposes, I was far from realizing the dimension the challenge that this step implied. I started my research in urban planning during the Urban Regeneration Master Program at the Technical University of Lisbon (TU Lisbon) where, by a gentle suggestion of Leonel Fadigas8, Jose P. Duarte 9 accepted to supervise my research, introducing me to a wider framework then I initially expected. This reality delayed the elaboration of the study, but it has also provided a deeper research context.
In fact, Jose P. Duarte brought up a unique
experience consolidated at MIT10, today widely recognized by the international community as a hub for the application of technologies to the field of architecture. Based on his own experience, Duarte proposed me to develop an ambitious project inspired in his work (Duarte 2007). The idea was simple and innovative: to create, in a similar way to the one he had devised for mass customized housing (Duarte 2003), a system for generating design proposals based on contextual criteria, but this time focusing on flexible urban plans. As in the system that Duarte invented for housing, it was necessary to create a structure involving three interdependent modules; one to formulate the urban program, one to generate spatial solutions, and another one to evaluate solutions according to programmatic criteria. Part of such a process, applied to the urban context, has already been tested by BeirĂŁo and Duarte (2005) with students from TU Lisbon. The pioneering experience was followed by the presentation of an article at the eCAADe conference in the same year (eCAADe 2005). This overall context led to the creation of the City Induction research project (CI), being the development of the formulation model - one of the project modules - my core task. Although some papers have already been published and presented at international conferences on this matter (Montenegro & Duarte 2008) (Montenegro & Duarte 2009), and on
6 . Jorge Rocha is a geographer, and lecturer assistant at the University of Lisbon (UL), Portugal. rd 7 . Ontology consists in the selected methodology of this research, and is described in the 3 chapter. Moreover an ontology is a data model that helps to support the development of the urban formulation model by providing a common vocabulary for users who need to share information in this specific domain. 8. Leonel Fadigas is an urban planner, landscape architect, and professor at the Technical University of Lisbon (TUL) , Portugal. Fadigas is the coordinator of the Urban Regeneration Master at the same university. 9 . JosĂŠ P. Duarte is an architect, scientist researcher, and professor at the Technical University of Lisbon (TUL), Portugal. Duarte is the coordinator of the City Induction project. His CV is available at: http://home.fa.utl.pt/~jduarte/ 10. The Massachusetts Institute of Technology (MIT) is a private research university located in Cambridge, Massachusetts. USA.
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related topics in collaboration with other of the project’s team members (Gil et al 2009) (Beirão et al 2009), this study comprises a wider research effort on the formulation field. More precisely, this work corresponds to a first volume that attempts to frame the context of the urban formulation model by providing its basic ontology. A further volume will be dedicated to the future implementation of such a model.
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This chapter describes the context, the problem, and the expected outcome of the research - The formulation model and the definition of its basic ontology.
Chapter 1 1. Introduction xiv
building a pre-design ontology: towards a model for urban programs
1.6.
Introduction This first chapter describes the context, the problem, and the expected outcome of the research.
1.7.
Research context As previously mentioned, the present study evolved simultaneously to the development of the City Induction project: a model to formulate, evaluate and generate urban plans. This R&D project aims at the integration of models areas within urban research; the urban formulation model, the urban evaluation model and the urban generation model. The basic idea is to create a full system to generate sustainable11 urban plans12. The interoperability of such system comprises the elaboration of a common ontology (a language13 based on ontological descriptions further explained in the 3rd chapter), which will provide the recursive tool used by the partial models to produce integrated results. This dissertation concerns a CI partial model: the formulation model14 and the definition of its basic ontology - a knowledge modelling structure15 to support the development and the management of urban programs. Such context helps to clarify the mission of the study.
formulation urban programs
1.
evaluation
generation design
evaluation
urban plans sustainable
The diagram depicts the basic process of interaction among the three partial modules of the CI project. However, the CI full model foresees more complex types of interaction.
11. A generally accepted definition of sustainability is described by ‘(…) the development that meets the needs of the present generation without compromising the ability of future generations to meet their own needs’. This definition has three key ideas: development, needs and future generations (Moughtin et al. 2003). 12. The model will be applied at a neighborhood scale, setting a vision for an urban extension at the site scale or within a new neighborhood centre. 13 . Language is a system of signs to express meanings (Chomsky 1965). 14. One will use the terms ‘pre-design’ and the more common term ‘planning’ interchangeably to refer to the formulation of the urban program. 15. In data modeling the task is to organize data so that it represents as closely as possible a real world situation, however feasible in computers’ representation. A data knowledge model encapsulates three main elements: objects’ structure, behavior and integrity constraints (Vazirgiannis & Wolfson 2001).
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1.8.
Problem Definition Any territory16 has potential that must be recognized and used in benefit of its population. This seems to be clear. However a large part of the urban problem is today a direct consequence of an inefficient use of the spatial resources (Sanchirico & Wilen 1999). By planning space, one can prevent the waste of resources allowing, at the same time, to maximize the satisfaction of population needs. Planning plays, therefore, a key role in spatial and social organization (D. Harvey 2009). First, because it defines objectives that clarify the mission of the territory, and second because it establishes levels of effectiveness and efficiency by implementing measures to attain defined goals (Drucker 2007). However, concerns related with urban planning surpass today the exclusive satisfaction of local needs. Today, there is the common belief that any population, in a limited space, contributes towards a balance at a higher scale (Hirst et al. 1996). This scale, that I will call global ecosystem17, seems to affect each portion of the territory, at the same time as each territory’s portion also seems to contribute to the global ecosystem (Pieterse 2009) - ranging from globalized financial markets (Lin & Mele 2005) to climatic global warming (Houghton 2005). In effect, humans pay today, for the first time in history, the global air that they breathe18 (Hoel 1991). The perception of this interdependence of scales is relatively recent in history, and current planning instruments are still not prepared to act in such a complex level (Terrados et al. 2007). In fact, there it seems to be a lack of mechanisms for providing the participants of the planning process with a set of efficient tools integrating multiple scales in order to respond adequately to current needs. This means that it is not enough to develop an instrument exclusively focused on the optimization of local resources (Buyya et al. 2005). It is necessary to create one that can be also capable to surpass local scale towards a more global consciousness. The diagram 2 depicts the timeline sketch of these changes. A computational platform, I would argue, can facilitate the creation and the management of such a more complex planning instrument.
16. Territory is a geographic area under control of a single governing entity such as state or municipality; an area whose bord ers are determined by the scope of political power rather than solely by natural features such as rivers and ridges (Britannica & inc. 2002). 17. An ecosystem is a system combined of organic and inorganic matter and natural forces that interact and change, intricate together by chains and cycles. It’s a sum greater than its parts. Its complexity and dynamism contribute to its productivity, but make it challenging to manage (Rosen 2000). 18 . CO2 international taxes and tradeable quotas (Hoel 1991).
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building a pre-design ontology: towards a model for urban programs
site site
site surrounding areas
(local needs)
surrounding areas timeline
2.
global
(concerns with surrounding areas)
(concerns at the planet scale)
Change of planning paradigms along time. First, a focus on local needs, then on spatial relations established between site and surrounding areas, and finally, a focus on a more global scale
This overlook constitutes a brief of a vast and complex context that will be addressed in the next chapters of this study. Meanwhile, it is useful to define some of the key concepts used in the study. EFFICIENT URBAN PROGRAMS: First is crucial to increase the existing levels of efficiency in the management of spatial resources in order to improve the quality of life of the population. Therefore is important to plan space throughout the development of efficient urban programs in order to attain defined goals. This is the first problem that this study aims to solve. However, is not the only one. SUSTAINABLE URBAN PROGRAMS: The current urban paradigm is recent and strongly related to a more global consciousness of urban problems. This means that it is necessary to create a tool for supporting the development urban programs from this particular perspective. URBAN PROGRAMS BASED ON A COMPUTATIONAL PLATFORM:
Finally, it is
important that such a tool, capable of generating efficient and sustainable urban programs, can be supported by a computational platform. Such platform allows one to act in a simpler and partially automated way, thereby enabling the planning participants an easier management of the contextual data.
The main argument that motivates the development of this study is therefore:
The creation of an efficient model for developing and managing sustainable urban programs, supported by a computational platform (the formulation model).
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Although based on basic principles, the initial mission of this study is far more complex. Urban planning deals with extended variables (Mabert et al. 2003), becoming difficult to establish the right ingredients to develop urban programs (Jabareen 2006). One way to solve the amount of information is to clarify it by creating a knowledge model called ontology (Gruber 2005) that permits to organize an extended database, relating all its components. Another complementary way is to describe the phase of the design process where urban formulation occurs - the pre-design phase (Best & De Valence 1999), to reveal the way programs are usually developed. To formulate urban programs is, therefore, crucial to organize a resourceful database, and understand how pre-design evolves within the design process (Lawson 2006). The title of this study - Building a Pre-Design Ontology - is a direct result of two research issues: a) the pre-design phase, and b) the ontology. However is important to keep in mind that the core subject behind those two issues is the formulation of sustainable urban programs. One will call this process Formulation Model (FM), and its development is the core of the present research. The diagram 3 depicts the frame of these main issues of the research.
Ontology knowledge database
Formulation Model creation of urban programs
3.
1.9.
PreDesign Phase
The core matters of the research: the pre-design phase, the formulation model, and the ontology
Proposed methodology It was mentioned above that the most efficient method to solve the problem of managing the extended data that is necessary process in the formulation model is through the development of an ontology (Gruber et al 1993). However, there are two different types of methodology to
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describe the formulation model, corresponding to different scales of approaching the research problem: a) the first, is the basic methodology that frames the overall process, that defines the core path for the work, and b) the second, is the applied methodology (an ontology), created in order to solve specific problems of the process (the formulation model process), as for example data management and definition of formulation rules. In this introductory chapter is important to describe the basic methodology of the research developed to accomplish the desired goals. The applied methodology will be described in the 3rd chapter. The basic methodology equates two structural concepts of the planning process: a) urban complexity19 (Healey 2007), which represents the main problem that this study aims to solve, and b) the quality of life of the population (QOL)20 (Maclaren 2004) that represent the main goal of the formulation model.
Such a methodology requires the creation of a system capable to uncover the urban complexity (the global problem) and its codification into a coherent set of rules that can be used for producing plans that ensure the quality of life of urban communities (the global aim). The solution for such a problem encompasses two steps: 1) to generate successful programs (formulation model) and, 2) to generate successful plans. The first corresponds to a pre-design phase, which is the aim of this study, and it can be diagrammed as follows:
19 . ‘Complexity is the physical fact of problems existing at multiple scales simultaneously. Complex systems solve these problems by adopting geometric structures that have structure at multiple scales simultaneously, that is to say fractal geometry. The architectural scientist Christopher Alexander elaborated on the link between fractal geometry and life by defining the theory of centers, which are parts or features that are distinguishable from the whole and cooperate with the wh ole to survive in the complexity of the universe. Because centers are themselves made of centers, they fit the recursive definition of fractals. Most important of all, complex structures can only be made through generative processes that draw from a previous step, repeated infinitely. The science of complexity is thus focused on discovering how things are produced, their final form being far too complex for one mind to fully grasp’ (Helie 2009). 20 . A Quality-of-Life (QOF) concept is: ‘The approach to the measurement of the quality of life derives from the position that there are a number of domains of living. Each domain contributes to one's overall assessment of the quality of life. The domains include family and friends, work, neighborhood (shelter), community, health, education, and spiritual’ - The University of Oklahoma School of Social Work (Notes on 'Quality of Life' Website).
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complexity of urban space
quality of urban life
• global problem
• global aim
urban programs predesign phase
4.
design phase
plan
Basic diagram: conceptual outline
1.10. Concerns involving the creation of the formulation model In the way is understood today, research should contribute towards society (Fritsch 2004). The evaluation of such contribution is generally located between the purpose and the relevance of the thematic field under study. In the case of this research, the best way to start exploring it is by answering a simple question: Why create a formulation model? Since the dawn of civilization, humans have made cities to support their societies. Although these urban settlements have been a source of progress, they have never been totally understood, relying on traditions and trial-and-error processes for their expansion. Attempts at planning and bringing them under the control of a planner have not entirely resulted yet (Hélie 2009). However, there is the relatively common belief that planning can be efficient in the sense that it can manage spatial resources to provide for QOL. In fact, the main work of planning, embodied by a large quantity of rules and codes (building, zoning, etc.), is essentially algorithmic 21 , and made up of if-statements. - If something: do this or that. So in this sense, creating the formulation model is a matter of developing protocols for how a city will grow (Helie 2009). But protocols must to be built upon
21 . ‘In mathematics, computing, and related subjects, an algorithm is an effective method for solving a problem using a finite sequence of instructions. Algorithms are used for calculation, data processing, and many other fields. Each algorithm is a list of well-defined instructions for completing a task. Starting from an initial state, the instructions describe a computation that proceeds through a well-defined series of successive states, eventually terminating in a final ending state’ (Blass & Gurevich 2003). 21a. ‘In computer systems, an algorithm is basically an instance of logic written in software by software developers to be effective for the intended "target" computer(s), in order for the software on the target machines to do something. For instance, if a person is writing software that is supposed to print out a PDF document located at the operating system folder "/My Documents" at computer drive "D:" every Friday at 10PM, they will write an algorithm that specifies the following actions: "If today's date (computer time) is 'Friday,' open the document at 'D:/My Documents' and call the 'print' function". While this simple algorithm does not look into whether the printer has enough paper or whether the document has been moved into a different location, one can make this algorithm more robust and anticipate these problems by rewriting it as a formal CASE statement or as a (carefully crafted) sequence of IF-THEN-ELSE statements’ (Kleene C. & Kleene C. 1936).
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building a pre-design ontology: towards a model for urban programs
theoretical models in order to support a development vision for a site or a region. That’s why the formulation model is so extremely dependent on the type of paradigms on which is builton (Clark 2000). If the paradigm fails so fails its program. Chapter 2 give an idea about the relevance of urban paradigms for the development of cities, within a large sort of perspectives. In the effort to understand the impact of urban paradigms on cuty growth, one even needs to consider those paradigms that aim to demonstrate the advantages of the absence of planning methods (Mintzberg 2000), by defending the emergence22 of urban morphologies along time, as a preferable option for urban space (Burgess & Park 2002). One fact seems to be clear. There are several models of urban programs used in the creation of urban plans. It seems also clear that some have failed tremendously23; and others have lacked implementation, remaining as theoretical guides24. Still, its common flaw appears to be the absence of crucial urban matters like sustainability factors. This has resulted, systematically, in the creation of inappropriate plans that are far from satisfying the necessities of the urban populations, and far from making an appropriate use of site features. But there are prime questions for such a framework. What are the main concerns behind the idea of producing a plan? The task of creating a good plan in order to increase the quality of urban life seems to be relatively easy at a first glance, by simply producing a full and resourceful program, built according to urban codes, regulations, and standard parameters. However the problem is more complex. Other urban programs have taken upon that task and have failed in the implementation of the plan. Creating a plan seems to be similar to the task of creating a language (Deacon 1998), or even to use a new language, requiring an additional effort to understand its new rules. In natural language (linguistics) there is an interaction between two crucial components: the semantics (the ideas), and the syntax (the form according to which as ideas are organized) (Chomsky 2002). Connecting the two, in order to create logic, is an
22 . ‘Emergence is the creation of systems of greater dimension than the elements that create it, sometimes also called selforganization, through the application of localized rules of action. The most elementary emergent systems are the binary, onedimensional cellular automatons studied by Stephen Wolfram that create complex fractals when shown in two dimensions. Emergence is also behind all forms of multicellular life, the cells of a plant or an animal following the instructions coded in their DNA to organize themselves into a much bigger organism. Those organisms will then also create emergent structures by following simple rules of action, like the termite cathedrals often used as an icon for emergence. Emergence is also behind human societies, from the invisible hand of economics (invisible because it is a dimension greater than any one of us) to the astonishing grow th of the Internet and later of Wikipedia. Studying the rules that enable emergence will allow us to build the systems to deal with the complexity of the universe (…) Urbanity is the cooperation and mutual-support of large numbers of people in close proximity. It is inevitably emergent, and to understand the science of emergence is the key to inventing the first fully emergent urbanism, capable of resolving all the complexities of a 21st century, sustainable city‘(Helie 2009). 23 . See a further explanation of the CIAM Athens charter’s principles, in the 2nd chapter. 24 . See a further explanation of the Alexander’s pattern language (1977) theory, in the 2nd chapter.
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building a pre-design ontology: towards a model for urban programs
enormous task, partially because the urban language (or the planning language) is not the natural language of human beings. Understanding and clarify it needs a supplementary research effort. However, this does not constitute the unique reason to envisage a good plan. What is then behind a proficient urban program? Embedding more knowledge into an urban program could be one of the answers. It is recognized that the urban environment is extremely complex because it involves an endless collection of matters and subjects, ideas, time, capital, and technology. All these subjects are too vast to compile and describe in short terms. Some studies took more than ten years and still have great difficulties in the implementation of the methodology. The first intuition is that such a task will never be accomplished. But the other preferable conclusion is that the task could be in fact achieved by a detailed survey focused on urban core concepts through a sequence of judicious steps. It is important to understand how such steps are processed and under which matters they rest. There are two ways of achieving this. The breadth and depth of such core concepts is further developed in the Chapter 2, describing the particular occurrences of recent history, and the impact it had on former urban programs. Chapter 2 is, thus, as an extension of the description of the problem definition just presented.
1.11. Expected outcomes and future work The objective is to create a formulation model that encloses two important aspects: a) One is the development of an ontology that is necessary to describe the urban space; first the context, and later the context with the solution, and which is also necessary to capture the structure of the planning framework. b) The second aspect is the description of the set of rules that describe the solution.
This goal of this study is closer to the first aspect - the development of a sketch of an ontology to describe the formulation model. In summary, one can say that this study provides the basic theory and some of the basic instructions for the functioning of the formulation model. Future work will concern the development of the mechanism that gives operability to the formulation model. There are relevant motives to proceed in such a sequence.
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building a pre-design ontology: towards a model for urban programs
Starting by creating a mechanism for a purpose whatever, without understanding its wide contextual framework induces often, the creation of efficient laboratory prototypes. This happens mainly because such prototypes are developed within a very limited context, with rules that are only efficient in such limited laboratory environments (Pickering 1992). Unfortunately, such prototypes are in general inefficient when dealing with real world problems. One of the main objectives of this research is precisely to capture the rules of interaction of urban phenomena in its wide context. The best way to trail such an objective is by start digging in the formulation framework in order to describe its basic structure. Thus, the study comprises two tasks: a) the first task is trying to understand the way formulation deals with a large amount of matters, b) the second task is to disclose the characteristics that can make it efficient when dealing with real urban plans. The complexity involved in the creation of the formulation mechanism25 is somewhat different. The specific methods and techniques required for its development demand it to be addressed in subsequent research. Future work will be based on the theory and the set of instructions proposed by this research, to make the model amenable to computer implementation. The goal is to sketch the prototype of such an implementation. How it will be made? The formulation model will be encoded into a description grammar26 (Stiny 1980) to establish a protocol with the generation model27 (shape grammars) of the CI project, which is being developed according to this theory28. The advantage of using grammars is that it provides the means to encode a certain degree of automated reasoning. One of the additional tasks is to allow the model to function with other formats, notations or platforms, in way to provide an ample base for a computational implementation. An ontology editor seems to be one of the model’s preferable platforms, because it can easily build up a bridge between the structure and rules of the model. In fact, some of the ontology software editors possess today a
25 . The formulation language will be the formulation operational tool developed to act in real or simulated urban contexts, supported by a computational platform. 26 . Description Grammar is a context-free grammar specialized for mathematical formulae. 27 . The generation model of the City Induction R&D project 28 . In a similar way it was used in Duarte mass customized housing.
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building a pre-design ontology: towards a model for urban programs
procedural framework to develop rules29, and also protocols for design solutions (Trento 2009). The straight linking process between data-taxonomic-structure (ontology class editor) and data-description-rules (ontology rules editor) allows one to eliminate part of the hard task of translation that usually occurs when is necessary to transfer information between different platforms. Following the encoding framework the model will be implemented and tested. This will be achieved by structuring the ontology, so that extensions or refinements of the model will be accomplished by adding or changing parameters, aiming at a flexible and sustainable data management. The idea is that the creation of the urban formulation model can be improved by using one or more case studies. In summary, the division of content between the present and the future work corresponds to the sequence shown in the diagram 5 as follows:
volume 1
volume 2
formulation 'theory and basic instructions'
formulation 'machine'
•descriptive (present work)
5.
•operative (future work)
Formulation research outline
1.12. Organization The current research is divided into a sequence of stages, each representing a defined task designed to achieve a specific goal and described in a specific chapter, as follows:
29 . ‘A ‘Knowledge Structure’ (KS) is composed of a set of Entities (…) dependent on a set of ‘Rules’.‘Rules’ can be classified in: • Reasoning Rules and Algorithms: formal codes for analysis, checking, evaluation and control of concepts associated to specific entities with inferential procedures of ‘If-Then’ type. • Codes, Laws and in force Rules: context dependant rules referred to the in force law that will become constraints for the entities which they are related to; • Consistency Rules: algorithms to check the consistency of values, parameters, attributes, instances, relationships and prop erties referring to the specific meanings associated to each entity in the specific context on which it is used; • Traditional Rules: non-formalized rules, practices and concepts that represent part of the reasoning process of each actor on his own specific disciplinary domain during the design process. By means of Inference Engines able to match rules among the ontologies - all of which formalized into a syntactically coherent IT structure - a deductive layer allows the designers to use in a coherent manner different levels of abstraction, or to exploit a conceptual interoperability (Calvanese D. et al, 2008). The dynamic and semantically-specific representation detecting incoherent/favourable situations by means of a constraint rule mechanism can allow them to be highlighted and managed in real time (Figure 3). At the same time it allows actors to make alternatives, more consciously reflecting on the consequences of their intents. In this way the impact of a networked ontology based system can make actors more aware of overall design problems, helping them in operating more participative and shared choices. ’ (Trento 2009) (continue. see annex 1 of this research)
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building a pre-design ontology: towards a model for urban programs
1st Chapter – Introduction - The first chapter describes the context, the problem, and the expected outcome of the research - The formulation model and the definition of its basic ontology. 2nd Chapter – Precedents - The contribution of this chapter is 1) to supply the context that leads to the necessity for elaborating a platform for urban programs and 2) to define the essential qualities of the urban design paradigm that such platform needs to support. The text describes theories and paradigms that implicit particular visions of how a city must be organized and, therefore, the specific forms of designing it that influence the substance of urban programs and the form of formulating them. 3rd Chapter – Methodology - This chapter describes a methodology for finding a solution for the following problem: How to develop a formulation model for urban programs? The creation of the formulation model requires the development of an ontology that can be used to describe the urban space; first the initial context, and later the context with the solution. The ontology, a knowledge database model, is also important to reveal the way in which urban programs can be structured. The contribution of this chapter is, therefore, to describe an urban ontology, which will provide the basis for supporting the development of the formulation model. 4th Chapter - Conceptual and Formulation Models - The objectives of the fourth chapter are: the description of the basic conceptual model and the description of the three parts of the formulation model: b1) the input, b2) the mechanism and b3) the output. 5th Chapter - The Formulation Process - The contribution of the fifth chapter for this research is: to describe the formulation process as well as the design phase where it occurs – the pre-design phase. The main objective is to provide a better understanding of the formulation framework and, at the same time, to generate the sketch of its semantic ground, that is, a consensual vocabulary to enable appropriate specifications (or the “communication acts”) towards design solutions.
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building a pre-design ontology: towards a model for urban programs
6th Chapter - The Sketch of a Planning Language - Language, like a seed, is the genetic system which gives our millions of small acts the power from the whole. The chapter 6 explores the most important category of the formulation model: the system language that is used by planners to formulate urban solutions. In summary, planner’s language. 7th Chapter - Conclusion
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building a pre-design ontology: towards a model for urban programs
01 •research mission
This research equates two core concepts of the planning process: a) The urban complexity, and b) The quality of life of the population. The goal is to create a system capable to uncover urban complexity (the problem) codified in a coherent set of rules that can be used to produce plans that ensures the quality of life of urban communities (the goal) – as depicted in diagram 6. complexity of urban space
quality of urban life
• global problem
• global aim
urban programs predesign phase
6.
design phase
plan
Basic diagram: conceptual outline
The title of this study - Building a Pre-Design Ontology - is a direct result of two research issues: a) the pre-design phase of the planning process where formulation occurs, and b) an ontology (a methodology that correspond to a data model). The core subject behind these two issues is the formulation of sustainable urban programs. The following diagram 7 shows these related matters in an interactive model.
Ontology knowledge database
Formulation Model creation of urban programs
7.
PreDesign Phase
The core matters of the research: the pre-design phase, the formulation model, and the ontology
The main goal that motivates the development of this study is the creation of a model for developing and managing sustainable urban programs, supported by a computational platform.
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building a pre-design ontology: towards a model for urban programs
The contribution of this chapter is 1) to supply the context that leads to the necessity to elaborate a platform for urban programs and 2) to define the essential qualities of the urban design paradigm that such platform needs to support. The text describes theories and paradigms that imply particular visions of how a city must be organized and, therefore, the specific forms of designing it that influence the substance of urban programs
and
the
form
of
elaborating them.
Chapter 2 2. Precedents
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building a pre-design ontology: towards a model for urban programs
2.1 Introduction The contribution of this chapter is: 1. to supply the context that leads to the necessity for elaborating a platform for urban programs and, 2. to define the essential qualities of the urban design paradigm that such platform needs to support. The text describes theories and paradigms that imply particular visions of how a city must be organized and, therefore, the specific forms of designing it that influence the substance of urban programs and the form of elaborating them.
2.2 The precedents An overview of the spatial transformations 30 that led to current urban environments allows one to understand how their present problems emerged. The objective is to take into account the course of urban actions in recent past to establish better solutions for future planning actions. This fact invokes the need to take a closer look at the space and time mechanism to extract the elementary laws for formulating urban programs. Why? Because urban programs can be reinforced by laws that respond efficiently to typical (sometimes recurrent) occurrences of space. This leads one to a pathway. The best way to extract laws - due to long-term process of urban transformations - is by depicting the context of the recent historical events. First, one will try to disclose a critical event for urban communities - the European chain of revolutions in the 18th century. In the 18th century European society changed dramatically. The chaotic city growth that followed the rural exodus caused by industrial revolution created the need for regulating such growth to prevent its flaws. However, such changes have deeper origins. In fact, the extensive mutation of political and geographic configurations that occurred in the modern era stemmed
30. Correspond to urban transformations, as well as the hybrid ones that are at the origin of the urban formations - even if not totally considered as urban.
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building a pre-design ontology: towards a model for urban programs
initially from the consequences of the French Revolution of 1789 31 . In this period, the foundation of the illuminist spirit and the Newtonian positivism transformed the organic structures of states into open systems, promoting the principle of equal opportunity, within a new democratic political framework. This paradigm had the following shortcomings; a cycle of social convulsions that shook European societies unchaining revolutionary movements, controlled by an intellectual nucleus located in France (Lefebvre & Evanson 1962). Territorial modifications were then largely implemented, and the birth of the “urban government” originated a new political order. With the free-ground concept, and the destruction of dominant models (monarchy and nepotism) 32 , the territorial borders of new states in formation build up drastic alterations within a new political and administrative space, sprouting new ownership relations, based on a new property domain outline. Property appeared then associated to an omnipresent battle for territorial ownership imposing the urgency to implement new laws, in order to control spatial transformations (Rossi 1984). This context was rapidly amplified by the technological dimension of the industrial revolution (Harvey 2006) which was commanded by private-initiative model, oppressing the ideals formed in the French Revolution of 1789. The way communities survived in the sprawling cities created by the industrial revolution evoked the necessity of creating an embryonic figure of urban government towards the implementation of laws and rules, in order to organize the urban environment (Rodrıguez et al. 2001, 415). Although the reaction to territorial flaws imposed the creation of new forms of government, the 20th century was marked by a quiet urban expansion developed without a critical support of communities. According to David Harvey (2006) “perhaps the chief sin of the twenty-century was that urbanization happened and nobody much either care or noticed in relation to the other issues of the day judged more important.” The establishment of participative urban political measures was therefore misled, according to Harvey, by self
31 . The French Revolution of 1789 was the ‘Revolutionary movement that shook France between 1787 and 1799 and reached its first climax there in 1789. Hence, the conventional term “Revolution of 1789,” denotes the end of the ancien régime in France, serve also to distinguish that event from the later French revolutions of 1830 and 1848. Although historians disagree on the causes of the Revolution, the following reasons are commonly adduced: (1) the increasingly prosperous elite of wealthy commoners— merchants, manufacturers, and professionals, often called the bourgeoisie—produced by the 18th century’s economic growth resented its exclusion from political power and positions of honour; (2) the peasants were acutely aware of their situation and were less and less willing to support the anachronistic and burdensome feudal system; (3) the philosophes, who advocated social and political reform, had been read more widely in France than anywhere else; (4) French participation in the American Revolution had driven the government to the brink of bankruptcy; and (5) crop failures in much of the country in 1788, coming on top of a long period of economic difficulties, made the population particularly restless’ (Britannica & inc. 2002). 32 . Nepotism, in politics, is when the relative of a powerful figure ascends to similar power seemingly without appropriate qualifications.
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building a pre-design ontology: towards a model for urban programs
exclusion of the critical mass of urban communities who avoided facing the extension of the urban problem. The result was an absence of efficient politics in urban governance, hence in plans. Despite the absence of communitarian participation, some European elites tried to develop new theories for organizing urban space, aiming to change social ideals. In 1933, with the Athens Charter published at the 5th CIAM 33 (Congrès International d’Architecture Moderne), the paradigms although seaming innovative and ideologically perfect to respond to a lack of collective beliefs, led to an uncontrolled sprawl, induced by mono-functional zoning program, which created a set of negative impacts on the urban environment. Several of the contemporary urban problems are still an indirect consequence of that paradigm or, as some modernists defend, is the result of an inefficient interpretation of the Charter’s philosophy. In the 1960’s, the Athens Charter began to be criticized, and urban communities embarked on a discussing of the post-war urban paradigms, mainly represented by a monofunctional model that had abundant implementations. In his book “framework of the invisible city” Mumford (1968) depicts a vision of such a model - a city built upon an impersonal “net,” essentially functional, characterizing an urban “Megamachine” that grows over nature by a dominant expansion of human activities. Jane Jacobs was a top figure of the sociologic movement that was spreading in opposition to the modernist vision. Some of her concepts concerning security, social cohesion, and communitarian participation (Jacobs 1961) are later embedded in several urban codes and programs. Amidst the critics of the “urban modernism” emerged a series of studies led by Christopher Alexander where the most known is A Pattern Language, (1977) which combined the design process with genetics34 and linguistics theory (Chomsky 1965). Its concepts mainly react to the repercussions of the zoning model that was embedded in the CIAM vision,
33 . ‘CIAM's early attitudes towards town-planning were stark: "Urbanization cannot be conditioned by the claims of a pre-existent aestheticism; its essence is of a functional order… the chaotic division of land, resulting from sales, speculations, inheritances, must be abolished by a collective and methodical land policy’ (CIAM). 34 . ‘- The idea that materialized in the published pattern language was first of all, of course, intended just to get a handle on so me of the physical structures that make the environment nurturing for human beings. And, secondly, it was done in a way that would allow this to happen on a really large scale. And, what I mean by that is that we wanted to generate the environment indirect ly, just as biological organisms are generated, indirectly, by a genetic code. Architects themselves build a very, very small part of the world. Most of the physical world is built by just all kinds of people. (…) How could one possibly get a hold of all the mass ive amount of construction that is taking place on Earth and, somehow, make it well, that means let it be generated in a good fashion and a living fashion. This decision to use a genetic approach was not only because of the scale problem. It was important fro m the beginning, because one of the characteristics of any good environment is that every part of it is extremely highly adapted to its particularities. in (The Origins of Pattern Theory - The Future of the Theory, and The Generation of a Living World, by Christopher Alexander, in a presentation recorded live in San Jose, California, in October of 1996, at The 1996 ACM Conference on ObjectOriented Programs, Systems, Languages and Applications (OOPSLA)) (Origins of Pattern Theory website).
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building a pre-design ontology: towards a model for urban programs
proposing a set of organized ideas related with the quality of the communitarian spaces, and the advantage of functional mixing applied to urban programs. The book describes a “planning language” designed to be applied across different scales, by applying specific patterns, in a sequence of steps, in a creative design process. The book encodes clear ideas about the quality of life of urban communities and gives instructions for how to achieve it by surveying urban problems and setting solutions for them. However, the Pattern Language theory, in contrast to the Athens Charter, had very limited implementation and planners had difficulties in applying the envisioned planning method. The results of the scarce implementation of the proposed language seem to be, in opposition to an axiom of the theory (the timeless way), recurrently stylistic and dated35. In the meanwhile, city growth and organization was strongly influenced by information technology. The “Informational City” presented in the “Theory of Space Flows” (Castells 2004), contributed for a refreshed vision of the organization of contemporary society by depicting it as a network society. The flows within a city referred by Castells “do not represent only one element of the social organization: they represent the processes that dominate our economic, symbolic, and politic life.” These invisible nets of communication, associated to the urban dispersion and the accumulation of information, led to form urban constellations like the North-American Edge-Cities (Garreau 1998). These cities encompass a group of incorporeal connecting networks (technology and software), as well as material nets (highways and roads). The interconnection of those two nets has originated a chaotic urban development. This chaotic growth presents difficulties to the recognition of patterns. However and according to James Gleick, (1987) the chaos can be object of study, using the “irregularity patterns” concept based on dynamics theory. The end of the traditional city was then announced as a victim of the deindustrialization and the depletion of local resources. It represents one of the deepest alterations in contemporary urban systems, that led to an increasing urban sprawl 36, defined by a territorial
35 . ‘- Although we intended that the pattern language would be generative, that is, would allow people to generate buildings and building designs, for themselves - truthfully, this does not happen. The patterns provide many profound ideas, and geometrical "nuggets": which are needed to make the environment work. But, as written in 1977, they do not actually allow a person to generate a good design, step by step. They do not place the emphasis on morphological unfolding, as they should’. (Pattern Language author website). 36 . Sprawl: ‘A haphazard and disorderly form of urban development. There are several elements that characterize sprawl: a) Residences far removed from stores, parks, and other activity centers, b) Scattered or “leapfrog” development that leaves lar ge tracts of undeveloped land between developments, c) Commercial strip development along major streets, d) Large expanses of low-density or single use development such as commercial centers with no office or residential uses, or residential areas with no nearby commercial centers, e) Major form of transportation is the automobile, f) Uninterrupted and contiguous low- to medium-
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building a pre-design ontology: towards a model for urban programs
dystopia37 (Harvey 2006) that generates a grid of distant economic free markets and sets out an invisible net that feeds some top-regions more technologically developed (Castells 2000), thus promoting an exclusion of the less developed ones. This fragmentation could have been prevented by the State in an early phase of reaction to such a powerful urban model, however, the State played a limited role (Stanlake & Grant 1994) facing the hegemony of monopolist companies, leading to the fall of the state-regulator figure, which dominated traditional cities before the last post-war (Harvey 2006). The end of the traditional city becomes hence a spatial transformation factor, where fragmentation emerges as a result of a continuous adaptation to a spatial model in constant development (Castells 2005). These dynamics appeared partially as a consequence of a dispersive free market model, in clear opposition to the previous industrial-localization. Quoting previous works, David Harvey (Harvey 1995:44) refers that capitalism as a production factor was specially developed to break spatial barriers, speeding up the “time” factor, with the intention of an exclusive accumulation of capital. Urban economy seemed then to influence crucial factors in the development of cities, generating new urban phenomena. The concept of privatization of the communal space and the lack of democratized access to cities, developed in “Splintering Urbanism” (Graham & Marvin 2001) is directly associated with the phenomena of social exclusion and stigmatization. This effect is well represented by the collapse of the traditional city of exchanges and interdependent markets, supplied by the neoclassical economy, and inspired in the prosperity of the organic and multifunctional medieval society. Salvador Rueda (1998) evokes this urban phenomenon concluding that it conduces to the death of Cities; “a planificación funcionalista y el mercado van creando espacios exclusivos según los niveles de renta, creando de nuevo un puzzle territorial, desconectando el tejido social y diluyendo el sentido que tiene la ciudad como una civis”. The contemporary city seams therefore to become a consequence of a globalized community, generating phenomena of inclusion and exclusion, deeply rooted in its particular economy and in strong technological development. Other theories described the welfare-state as a model that sprouted a group of bureaucratic instruments in an attempt to solve the urban expansion phenomenon, assuring
density (one to six du/ac) urban development g) Walled residential subdivisions that do not connect to adjacent residential development’ (Evans et al. 2007). 37 . A dystopia (from the Greek δυσ- and τόπος, alternatively, cacotopia, kakotopia, cackotopia, or anti-utopia) is the often futuristic vision of a society in which conditions of life are miserable and characterized by poverty, oppression, war, violence and/or terror, resulting in widespread unhappiness, suffering, and other kinds of pain. (Harper & Harper, Douglas n.d.)
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building a pre-design ontology: towards a model for urban programs
an accomplishment of a classic planning dichotomy - “agreed goal” and “known technology”(Christensen & Bang 2003); a perfect functional and closed system. This system, supported and strengthened by the modernist ideals, defined a rigid set of goals and techniques in order to implement plans. Christensen defends that such dichotomy, although effective during a specific period of time, falls upon social dynamics, due to its relative inflexible administration. A group of concepts defined in the “Governance of Europe’s City Regions,” highlights the need for the implementation of flexible policy in order to produce more efficient plans, acting as a reaction to the classic welfare-state conceptions. In fact, the changing nature of regions moving from fixed territory (spatial container) to regional groupings of specialized production clusters, requires flexible policy responses (Herrschel & Newman 2002). Flexible plans appeared therefore to act as the natural reaction to the dynamic character of the contemporary urban reality, guaranteeing a balance between the public and the private sectors (within their particular interests), towards a “common good” and “public interest” (Healey 2007). Plans can thus be executed efficiently (Christensen & Bang 2003) by implementing flexible models supported by local communities, acting as a protective shell against the unpredictable dynamics of the urban space.
2.3 Conclusion In summary one can say that until the 19th century the problem was situated within geographic borders, and after the 60’s decade of the 20th century concerned a much different subject - the collapse of the traditional city, and a change imposed by market laws, the zoning concept, and the free economy model, promoting an endless functional grid involving the expansion of the urban structure. It is also manifest that at the beginning of the 21st century, another core discussion appeared on the research bench; the development of an abstract “urban net” within a new theory of space - “the informational net” (Castells 2003) - an invisible network connecting new urban space formations. Hence, while prior to the 19th century the urban phenomenon was related essentially with the physical and visible aspects of property (Rossi 1984), the post-war conceptions appeared to involved a more complex and dynamic problem the difficulty of a physical recognition of the urban structures in expansion (Portas et al. 2003: 221); partially attributed to the spreading of an incorporeal society network (Castells 2005) and to a specific economic model. The immateriality of the contemporary urban space is, in the words of João Ferrão (Portas et al. 2003), part of the “real city today”; an unrecognized city
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building a pre-design ontology: towards a model for urban programs
due to the fact that it appears to be morphologic and politically invisible. More recently numerous group of researchers are pointing out to climatic factors and energy resources as key issues of urban planning, responding to increasing global concerns as are the climatic changes (Houghton 2005). Throughout all these periods, the concerns of planners with solving urban problems changed dramatically; and several experiences on the field, following new urban theories (as in the CIAM vision), caused even more problems, creating a sense of a global collapse. Despite all efforts and failures, important planning concepts remained more or less consensual;
1. The first concept represents a repercussion of the Industrial Revolution, establishing the need to regulate urban space to guaranty the quality of urban life - urban goals, rules, and guidelines. 2. The second concept describes the need for implementing a more multifunctional and organic urban system, refuting the hegemonic economic model of the dispersive free market, and the modernist CIAM vision - mix-uses/ social space/ participation. 3. A third concept describes a flexible system within urban plans, capable of absorbing the social mutations, reacting to the unpredictable dynamics of the urban phenomena - flexible programs, 4. The fourth concept describes the relevance of the sustainability factor, as a balance between all factors of the urban phenomena, including the economic, social, energetic and climatic factors - sustainable programs. As a result, today is more or less consensual that urban programs should: a) be regulated by goals, rules and constraints, b) be multifunctional, c) be participative, d) be flexible, and e) be sustainable. These are the features that the study City Induction project tries to respond to and this research is concerned with the development of a formulation model according to the same principles.
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building a pre-design ontology: towards a model for urban programs
02 • urban programs - the main laws
It is more or less consensual that urban programs should: a) be regulated by goals, rules and constraints, b) be multifunctional, c) be participative and collaborative, d) be flexible, and e) be sustainable. These are the features that the formulation model tries to respond to. The diagram 8 shows the interaction of the main laws of urban programs depicted in this chapter.
participation and collaboration
sustainability
multifunctionality
8.
goals, rules and constraints
flexibility
The main laws of urban programs
Urban programs core structure: 1. Rules and Constraints | goals, rules and constraints 2. Multifunctionality 3. Participation 4. Flexibility 5. Sustainability
| diversity and mixture | involvement of communities | strategies for future actions (change of uses and concepts) | environmental and social philosophies
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building a pre-design ontology: towards a model for urban programs
This
chapter
describes
a
methodology to find a solution for the following problem: How to develop a formulation model for urban programs? The contribution of this chapter is to describe an ontology, which is the selected methodology to support the development of the formulation model.
Chapter 3 3. Methodology
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building a pre-design ontology: towards a model for urban programs
3.1. Introduction This chapter describes a methodology to find a solution for the following problem: How to develop a formulation model for urban programs? The creation of the formulation model encloses an important aspect - the development of an ontology that is necessary to describe the urban space; first the context, and later the context with the solution. The ontology is also important to reveal the way formulation model can be structured in order to establish communication protocols within the planning process, that is, the process of generating the urban program from the context. The goal of the study in which context this thesis evolves is therefore to find a solution for the formulation model. The solution for this problem includes two steps: one is the development of an ontology to describe urban space, as well as the ontology of the mechanism by which a program is generated from the analysis of the context; and the other is the inference of the mechanism itself, that is, of the rules that composed it. This chapter is concerned with the development of the ontology to describe urban space. The ontology corresponds basically to at a knowledge based model applied to urban programs. The outline and the details involving such methodology will be described in this chapter.
3.2. Adopted methodology The planning process requires the establishment of an adequate communication with stakeholders, to share ideas within a planning team, or to present a strategy to a community. Urban formulation - an important part of the planning process - requires a method to select and organize data that describes the urban context, to generate a description of the solution for that context, and to share and communicate the solutions to the stakeholders. An ontology, a Knowledge Representation (KR) model is a data modelling process or a language that is capable to represent and convey such type of information (Caneparo et al. 2007). KR is not a “picture� of the problem, but rather a device for the attainment of knowledge about it (Kaplan, 1963). Indeed, sometimes the most important outcome of a data modelling process (here represented by an ontology) may not be the process itself, but rather the insight one gains as one struggles to articulate, to structure, to critically evaluate, and agree upon it (Moore & Agogino, 1987). “Therefore, the purpose of the modelling process - an ontology - is
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building a pre-design ontology: towards a model for urban programs
not only a proper representation of a process but rather how this process can help one to better understand the domain of knowledge represented in it” (Luca 2007). What is an ontology? The concept comes from a theory that concerns the study of existence born from the legacy of the Aristotelian philosophy meaning “a systematic explanation of the existence” (Gruber et al 1993). The “Aristotelian ontology offers primitive categories, such as substance and quality, which were presumed to account for “All That Is”. Ontologies, in general, are created to facilitate the understanding about a specified a domain by defining its entities, its classes, its functions and the relationships between all those (Fonseca & Egenhofer 1999). Despite its philosophical legacy, the ontology described in this research is related with a technical term and method that is used in computer science. Why create an ontology? An ontology is a resourceful data model that helps to support the development of the urban formulation model by providing a common vocabulary for users who need to share information in this specific domain (Sachs et al. 2006). In addition, an ontology is an accurate mechanism to explicit and increase the knowledge about a specific subject matter, in the case of this research concerning urban space as well as the set of solutions to intervene in it. Some of the reasons to create an ontology are: 1. A share of a common understanding of the structure of information among people or software agents, 2. To enable the reuse of the domain knowledge, 3. To make domain assumptions explicit, 4. To separate domain knowledge from operational knowledge, and finally 5. To analyze domain knowledge. In the context of the formulation model such process permits to: 1. Create a common shared structure of information to support urban programs, 2. To recycle such information in order to use it recurrently in different urban contexts, 3. To explicit the formulation concepts by defining the way entities operate within the ontology, 4. To separate the domain conceptions from the urban operative descriptions, and 5. To assess the data model in order to improve the pre-design ontology (Noy et al. 2001).
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building a pre-design ontology: towards a model for urban programs
How to create an ontology? The best method to create an ontology is with an ontology editor which is a software platform composed by three basic blocks that include: 1) classes, 2) slots (sometimes also called roles or properties), and 3) facets (sometimes called role restrictions). An ontology of such type together with a set of individual instances of classes constitutes a knowledge base (Sachs et al. 2006). There is no one correct methodology, nor is there a single correct result for developing ontologies. “Developing an ontology is an iterative process. Usually one can start with a rough first pass at the ontology, and then revise and refine the evolving ontology in order to fill in the details” (Noy et al. 2000). In practical terms developing an ontology includes: 1) defining classes in the ontology, 2) arranging the classes in a subclass-superclass hierarchy, 3) defining slots and describing allowed values for these slots, and 4) filling in the values for slots for instances. The undertaking of the production of ontologies is according to Smith and Mark, (Fonseca & Egenhofer 1999): 1) to help to understand the way different communities share information, 2) to help to discover certain distortions in the cognitive processes of conception of the world, and 3) to supply patterns towards the development of a process.
3.3. Ontologies within computer science - (AI) Artificial Intelligence Due to its capabilities, ontologies have been adopted in many business and scientific communities as a way to share, reuse and process domain knowledge. “Ontologies are now central to many applications such as scientific knowledge portals, information management and integration systems, electronic commerce, and semantic web services” (McGuinness et al. 2000). This demonstrates the potential of ontologies within computer science. In this application field the ontology term denotes a method that is designed for a purpose, which is to enable the modelling of knowledge about a real or imagined domain. Gruber (1993) describes in a very explicit way how to develop ontologies and the implications of such method. He noticed that the term had been adopted by early Artificial Intelligence (AI) researchers, who recognized the applicability of the work from mathematical logic (McCarthy 1980). He also noticed that AI researchers could create new ontologies as computational models that enabled certain kinds of automated reasoning (Hayes-Roth 1985). Gruber refers that “in the 1980's the AI community came to use the term ontology to refer to both a theory of a modelled world (Hayes 1979) and a component of knowledge systems; referring that
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building a pre-design ontology: towards a model for urban programs
“some researchers, drawing inspiration from philosophical ontologies, viewed computational ontology as a kind of applied philosophy” (Sowa 2000).
3.4. Ontology Interoperability It was patent in an effort, in the early 1990's, to create interoperability standards by identifying a technology stack that called out the ontology layer as a standard component of knowledge systems (Neches et al. 1991). “A widely cited web page and paper associated with that effort is credited with a deliberate definition of ontology as a technical term in computer science” (Gruber et al. 1995). The paper defines ontology as an “explicit specification of a conceptualization,” which is, in turn, “the objects, concepts, and other entities that are presumed to exist in some area of interest and the relationships that hold among them.” While the terms specification and conceptualization have caused much debate, the essential points of this definition of ontology are, according to Gruber that: 1) an ontology specifies the concepts, relationships, and other distinctions that are relevant for modelling a domain, and 2) the specification is in the form of definitions of representational vocabulary (classes, relations, and so forth), which provide meanings for the vocabulary and formal constraints on its coherent use. One of the essential characteristics of the ontologies is the sharing of information - the shared knowledge, which allows the creation of common systems. The advantage is to provide an integration of different studies on the same substance of inquiry, through a recurrent general procedure. This focus allows and prevents ambiguities between results. However the difficulties caused by the heterogeneities of the information have invoked an increased necessity of creating a science of integration (Fonseca et al. 2002). According to Fonseca and Egenhofer (1999) the elaboration of ontologies requires also the participation of diverse entities in permanent interaction. They described the key elements of such system by; “container” (container of objects from diverse sources), “data repository” (within a defined research and classes), “user interface”, and the “ontologies” (dynamic structures - objects in a pattern catalogue). In such scheme, these forms are mediated by the “coordinator”.
3.5. Representation of ontologies The ontology allows one to act within two differentiated and complementary levels: the “top level ontology” (Guarino 1997) where the concepts and the macro scale relations are located; and the “application ontology”, where are specified the concepts describing the nature of its
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building a pre-design ontology: towards a model for urban programs
particular interactions. The “top level ontology”, as mentioned, describes relations at a macro scale – for example the core components of the pre-design phase. The “application ontology” specifies particular concepts belonging to particular fields which include detailed tasks - for example the urban codes of the pre-design phase. The representation of ontologies can also be expressed through standard associations (Novello et al. n.d.) to qualify the relations between entities, namely: taxonomy (is a, type of), partonomy (part of), mereology (“part-ofall” theory), chronology (precedents between concepts) and topology (theory of limit and border). Moreover, ontologies can be represented by; a) dominions, which describes the vocabulary used in a specific field of knowledge; b) tasks, which describes the vocabulary used in a specific activity of a field; and c) representations, which explains the concepts of formal entities. Urban ontologies are usually called spatial ontologies, due to its relevant spatial descriptions. The development of research in the field of spatial ontologies has created a specific lexicon and a theoretical structure, to responds to the specific demands of spatial domain. Smith and Mark (1999) purposed the creation of spatial ontologies with the objective of getting a better understanding concerning the geographic world. The same authors allege that the use of this type of ontologies can assist users in the exchange of information preventing distortions from human cognition, which is a recurrent idea in the creation of generic ontologies. To Pinho and Goltz (n.d.) the geographic objects, that are the spatial fundamentals of the urban space, can be divided in two types, defined by the Latin axioms Bona Fide and Fiat. The first type congregates objects that possess a physical delimitation more or less accepted between people of different cultures. They are tangible objects as a road, a mountain, or a lake. In opposition Fiats referrers to objects with abstract limits. Such Fiats can be divided by 1) Fiats and vagueness that are geographic objects that do not possess a well-defined border, and were limits are diluted in space, b) Consensus Fiats that are objects that have its existence on a consensual form by given information from inhabitants in a determined area, c) Legal fiats that are objects that have their limits defined on some legal basis, as the land use or the airspace, and the GIS fiats that are objects generated from the mathematical logic of the GIS. The development of the diagram (9) is inspired in the urban plot diagram developed by Pinho and Goltz [n.d.]. This diagram aims to explain some types of entities that compose an ontology, in this case involving urban patterns.
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building a pre-design ontology: towards a model for urban programs
inanimate objects is
geographic object
common object
is
fiat
bona fide
is part of
legal fiat
GIS fiat
urban codes
9.
consensus fiat
GIS data
field analysis
fiat and vagueness private space (example)
urban patterns
Example of an urban pattern top level ontology. This diagram is inspired in the urban plot diagram developed by Pinho & Goltz [n.d.]
3.6. Editing ontologies As aforesaid the best method to create an ontology is with an ontology editor. But what is an ontology editor? According to Sachs (2006) an ontology editor is an integrated software tool used by system developers and domain experts to develop knowledge-based systems. The applications developed with an ontology editor are generally used in problem-solving and decision-making in a particular domain. In the case of this research the problem is focused on the urban space phenomena, and the decision-making on the set of solutions to implement in such a space in order to support sustainable communities. Where to start? One might start by determining what the ontology is going to be used for, and how detailed or general the ontology is going to be. In this thesis the objectives is clear: to define a formulation model for urban programs. Such ontology, in a primary phase, will describe basically the general concepts of the formulation model, and eventual methods to categorize its entities.
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building a pre-design ontology: towards a model for urban programs
There are several viable alternatives for creating the ontology. One of the first steps will be to determine which alternative would work better for the projected task, be more intuitive, more extensible, and more maintainable - remembering that an ontology is a model of a real domain in the world, ant that the concepts in the ontology must reflect this reality. After defining an initial version of the ontology, one can evaluate and debug it by using it in applications or problem-solving methods or by discussing it with experts in the field. Such a framework is crucial to develop the formulation model. “As a result, one will almost certainly need to revise the initial ontology. This process of iterative design will likely continue through the entire lifecycle of the ontology” (Sachs et al. 2006). To explicit the functioning of an ontology editor it will be develop an example with the Protégé editor (Noy et al. 2001) following the trail of its tutorial. The case is simple. Suppose one wants to develop an ontology for climatic patterns. The “examples/climatic patterns” subfolder of the ontology editor installation directory contains a completed Editor-Frames project, - urban climatic patterns, which provides one possible ontology for this domain. Some of the questions one want to answer are: 1. What are the components responsible for each climatic pattern? 2. What is the content of each pattern, and what is the theory behind it? 3. To what matters each pattern is related with? 4. What is the layout of each pattern? Once one has an idea of what one wants to cover, one can list some of the important terms needed. These can include basic concepts, properties they might have, or relationships between them. To begin with, one can just collect the terms without regard to the role they might play in the ontology. In the climatic patterns example one have particular patterns. Each one contains content such as “type of climatic aspect that is covered” and “applicability” and it has a theory behind it that is responsible for the validity of its existence. Each pattern has a form, and that form may or may not be material. For each material pattern, one wants to know its name and subject, and to what it relates with. As one continues to generate terms, one are implicitly defining the scope of our ontology, by deciding what to include and what to exclude. For example, upon initial examination of the term material pattern, one might want to add “sun protected windows” or “wind impact on streets”. However, upon reflection, one might realize that one wants the ontology to focus on the costs associated with the content of the “sun impact on buildings”. Therefore, one would decide not to include “wind impact on
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building a pre-design ontology: towards a model for urban programs
streets” as a term of interest. When one has a fairly complete list, one can start to categorize the different terms according to their function in the ontology. Concepts that are objects, such as “pattern” or “site application”, are likely to be best represented by classes. Properties of the classes, such as “wind” or “sun”, can be represented by slots, and restrictions on properties or relationships between classes and or slots, are represented by slot facets (Noy et al. 2000). Above is shown an example of the development of a climatic pattern in the Protégé editor. The example presents cold region patterns.
10. Protégé edition of a climatic pattern
11. The visualization tab of the cold region edited by the Protégé editor
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building a pre-design ontology: towards a model for urban programs
12. In the left is shown the class hierarchy of the climatic patterns ontology. In the top right is shown the type of role of each class (related with a different symbol) – abstract or concrete. In the bottom right is shown an instance slot (bioclimatic pattern slot) where one can fill up all required data
3.7. Comparing ontology editors: Ontolingua and Protégé The Ontolingua editor was developed by the Knowledge Systems Laboratory of Stanford University (KSL), and it offers a set of program tools that allows the editing of ontologies. The system is referred to by several authors, amongst them, Fonseca and Egenhofer (1999). Ontolingua is an online software where web sessions are authorized for registered users. The Stanford KSL Ontology Editor allows, through a set of procedures, to create series of axioms, made within a hierarchy of classes, and associations of “Examples” or individual “Instances”, establishing “Functions”, “Facets” e “Slots” as schematic entities. This comprises the basic vocabulary of the Ontolingua Editor. The generation of these entities is clarified by the program’s tutorial (Farquhar 1997), within a set of suggestions and guidelines for the development of ontologies, namely; “1) to write a few sentences describing the ontology including the general subject area that is intended to cover with the ontology, 2) to make a list of what one would like to state in the ontology, 3) to make a list of the concepts that one think should be included in the ontology, 4) to look for ontologies in the library of ontologies that may contain terms which one can use to develop the ontology, and5) review and make modifications to one’s lists as needed throughout these steps” (Farquhar 1997).
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building a pre-design ontology: towards a model for urban programs
Like the Ontolingua editor, the Protégé editor is a free, open-source platform that provides a growing user community with a set of tools to construct domain models and knowledge-based applications with ontologies. One of its advantages is the plain access to formats and protocols towards the creation of resourceful data models. The Protégé implements a rich set of knowledge-modelling structures and actions that support the creation, visualization, and manipulation of ontologies in various representation formats. Protégé can be customized to provide domain support for creating knowledge models and entering data, appearing to be friendlier than the Ontolingua in the management of its platform. Furthermore, Protégé can be extended by way of a plug-in architecture and a Javabased Application Programming Interface (API) for building knowledge-based tools and applications. The Protégé platform supports two main ways of modelling ontologies: 1) The Protégé-Frames editor enables users to build and populate ontologies that are frame-based, in accordance with the Open Knowledge Base Connectivity protocol (OKBC). “In this model, an ontology consists of a set of classes organized in a subsumption hierarchy to represent a domain's salient concepts, a set of slots associated to classes to describe their properties and relationships, and a set of instances of those classes - individual exemplars of the concepts that hold specific values for their properties” (Sachs et al. 2006). 2) The Protégé-OWL editor enables users to build ontologies for the Semantic Web, in particular in the W3C's38 Web Ontology Language (OWL). “An OWL ontology may include descriptions of classes, properties and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. These entailments may be based on a single document or multiple distributed documents that have been combined using defined OWL mechanisms”. Protégé ontologies can be exported into a variety of formats including RDF39(S), OWL, and XML Schema40. Protégé is
38 . W3C: World Wide Web Consortium. 39 . The RDF data model is similar to classic conceptual modeling approaches such as Entity-Relationship or Class diagrams, as it is based upon the idea of making statements about resources (in particular Web resources) in the form of subject-predicate-object expressions. These expressions are known as triples in RDF terminology. The subject denotes the resource, and the predicate denotes traits or aspects of the resource and expresses a relationship between the subject and the object. For example, one way to represent the notion "The sky has the color blue" in RDF is as the triple: a subject denoting "the sky", a predicate denoting "has the color", and an object denoting "blue". RDF is an abstract model with several serialization formats (i.e., file formats), and so the particular way in which a resource or triple is encoded varies from format to format. http://www.w3.org/TR/PR-rdf-syntax/ "Resource Description Framework (RDF) Model and Syntax Specification". 40 . An XML schema is a description of a type of XML document, typically expressed in terms of constraints on the structure and content of documents of that type, above and beyond the basic syntactical constraints imposed by XML itself. These constraints are generally expressed using some combination of grammatical rules governing the order of elements, Boolean predicates that
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building a pre-design ontology: towards a model for urban programs
based on Java, is extensible, and provides a plug-in environment that makes it a flexible basis for rapid prototyping and application development. “Protégé is also supported by a strong community of developers and academic, government and corporate users, who are using Protégé for knowledge solutions in areas as diverse as biomedicine and intelligence gathering. Protégé is a U.S. national resource for biomedical ontologies and knowledge base supported by the U.S. National Library of Medicine, and is a core component of The National Centre for Biomedical Ontology, within the Stanford Centre for Biomedical Informatics Research” (Noy et al. 2000).
the content must satisfy, data types governing the content of elements and attributes, and more specialized rules such as uniqueness and referential integrity constraints.
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building a pre-design ontology: towards a model for urban programs
03 • an ontology (a data model) is a good way of describing the pre-design phase of the urban design process. •an ontology helps with the creation and management of urban programs. The objective is to create a model that encloses the development of an ontology to describe the urban space; first the context, and later the context with the solution. The objective is to make use of an administrative tool that helps to create and manage urban programs. The framework is described in the following diagram scheme.
1 •problem how to develop a predesign model to launch sustainable urban programs
3
2
•management tool
•methodology
classes slots instances
relational rules
data
sorted data
helps to create and manage urban programs
phases procedures
rules constraints
attributes
data knowledge model (an ontology editor)
13. Methodology framework
Methodology (management tool): 1. Problem 2. Methodology 3. Management tool
|Complexity of urban data |Organizes data elements to facilitate understanding |Help with the creation and management of urban programs
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building a pre-design ontology: towards a model for urban programs
The objectives of the fourth chapter are: a) the description of the basic conceptual model, and b) the description of the three parts of the formulation model: b1) the input, b2) the mechanism, and b3) the output.
Chapter 4 4. Conceptual and Formulation Models
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building a pre-design ontology: towards a model for urban programs
4.1. Introduction The objectives of the fourth chapter are: a) the description of the basic conceptual model, and b) the description of the three parts of the formulation model41: b1) the input, b2) the mechanism, and b3) the output.
4.2. The conceptual model The basic conceptual model represents the core concept of this research, and the goal of this chapter is to explain it. The conceptual model describes the structure of the formulation process and is inspired in a more global mathematical model invented by Duarte (2003) for developing interactive systems for generating design solutions. Duarte’s model is called discursive grammar, and it includes a program system for formulating the design brief based on contextual data, a design system for generating a solution that matches the brief, and an evaluation system for guaranteeing that the brief fits the context and the solution matches the brief (Diagram 14). The program or formulation system is encoded by a description grammar (Stiny 1981), whereas the design system is composed of a description and a shape grammar (Stiny 1980). The evaluation system compares the description in the design brief with the description of the evolving design. A set of heuristics is then used to guide the generation of solutions towards to ensure that the solution’s description matches the brief’s description. The model developed in this research explores the “formulation system” (the first module in Duarte’s model), adapting it to the urban context, and introducing additional functions, such as a clear definition of the design brief ‘s description structure by means of an ontology and its encoding using an ontology editor.
41. The ‘formulation’ term, in this research, denotes the planning framework of producing an urban program (and also its process). Formulation occurs during the ‘pre-design phase’ and it corresponds to an initial phase of the urban design process where the actions to intervene in the urban space are planned by deriving the program from the context.
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building a pre-design ontology: towards a model for urban programs
portuguese housing evaluation system Pedro, 2000
context
portuguese housing program system
program
Pedro, 1999 Description grammar (Stiny, 1981)
Siza’s Malagueira design system
design
Shape grammar (Stiny and Gips, 1972)
14. Duarte’s model (discursive grammar for housing) based in three theories (Stiny 1981), (Pedro 2001a) and (Stiny & Gips 1972)
1. INPUT
Read Data (urban context)
DATA COLLECTION
2. INTERPRETER
Interpretation of data
MECHANISM (for generating the program)
3. OUTPUT
Define Specifications (for design)
PROGRAM (design brief)
As in Duarte’s model, in FMo there is a clear path information flow between the three basic functions or components of the model, as shown in Diagram 15. information path
INTERPRETER •design specifications
•contextual data
•machine
INPUTS
OUTPUTS
information path
15. The conceptual model of the urban formulation process (FMo)
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building a pre-design ontology: towards a model for urban programs
Model’s functioning In a sense, the conceptual model is a representation of a “computational procedure that takes some value or set of values, as inputs and produces some value, or set of values, as output” (Cormen et al. 2001). One can also argue that, informally, this process corresponds to an algorithm which is any well-defined computational procedure based on data exchanges - a sequence of computational steps that transform the input into the output. An algorithm that can also be interpreted as a tool for solving a well-specified computational problem - a problem here focused on the generation of urban solutions. As mentioned, the algorithm describes a specific computational procedure for achieving the input/output relationship. For example, one might want to sort a sequence of numbers in decreasing order. This problem arises frequently in practice and provides a ground for introducing standard design techniques. Alexander’s Pattern Language (Christopher Alexander et al. 1977) was created under a similar conceptual structure. Here is how one formally can define a sorting problem: Input: A sequence of n numbers a1, a2,..., an . Output: A permutation (reordering) a’1, a’2,..., a’n of the input sequence such that a’1 a’2 ... a’n. Given an input sequence 41, 61, 79, 36, 61, 78, a sorting algorithm returns as output the sequence 36, 51, 61, 61, 78, 79. Such an input sequence is called an instance of the sorting problem. In general, an instance of a problem consists of the input (satisfying whatever constraints are imposed in the problem statement) needed to compute a solution to the problem. The input corresponds to urban contextual data, being the constraints part of its interpretation. The solution corresponds thus to the interpretation output, which in this case corresponds to specifications for design solutions. An algorithm is said to be correct if, for every input instance, it halts with the correct output. Cormen (2001) says that a correct algorithm solves the given computational problem, as an incorrect algorithm might not halt at all on some input instances, or it might halt with an answer other than the desired one. An algorithm can be specified (in computer science) as a computer program, or even as a hardware design. The requirement is that the specification must provide a precise description of the computational procedure to (Cormen et al. 2001) - if something, then do something - the recurrent concept of the urban formulation framework. Now, a closer look at the model’s basic components:
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building a pre-design ontology: towards a model for urban programs
INPUT: The first component of the conceptual model (Data) corresponds to the set of information that is gathered to describe the urban space (among other contextual information). Data corresponds to the set of information collected on the site and the local population, as well as on the promoter’s features, mandatory requirements, or ideas about the plan’s development. INTERPRETER: The Interpreter42 corresponds to the core of the model - a centre of data exchange and interpretation (analysis, conversions, and synthesis). The Interpreter defines the flow between the contextual data and the final list of requirements or ingredients that will be used as patterns for design. OUTPUT: The third component corresponds to the set of specifications that will help to described spatial solutions (organization, shape, and morphology). The data structure43 organization of the output data (its ontology) is particularly important. An adequate formulation ontology (the structure of the urban program) will facilitate the generation of better solutions as it facilitates the flow between descriptions (urban program) and generation (urban solutions). Model descriptions will be created on the foundations provided by the Alexander’s Pattern Language theory.
4.3. The formulation model The formulation model (FMo) is the detailed structure of the conceptual model that enfolds a simple sequence of ideas, that is; a) a problem is perceived (the urban context), b) thus emerges the need to intervene to solve the problem,
42 . A classical translating machine stands with one foot on the input text and one on the output. The input text is analyzed by the components of the machine that make up the left leg, each feeding information into the one above it. Information is passed from component to component down the right leg to construct the output text. The components of each leg correspond to the chapters of an introductory textbook on linguistics (…), then syntax, semantics, and so on. (…) We cannot be sure that the classical design is the right design, or the best design, for a translating machine. But it does have several strong points. Since the structure of the components is grounded in linguistic theory, it is possible to divide each of these components into two parts: a formal descrip tion of the relevant facts about the language, and an interpreter of the formalism. The formal description is data whereas the interpreter is program. The formal description should" ideally serve the needs of synthesis and analysis indifferently. (…) (Kay 1984). 43 . A data structure is a way to store and organize data in order to facilitate access and modifications. No single data structure works well for all purposes, and so it is important to know the strengths and limitations of several of them (Luger 2005).
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building a pre-design ontology: towards a model for urban programs
c) however the problem needs to be made explicit to enable the development of solution(s), d) thus it has to be created a path towards solution(s), e) this requires the creation of an instrument to manage the e1) contextual data, e2) the interpretation of the problem, and e3) the coding of specifications for the solution(s).
The formulation model consists of the instrument to solve this finite sequence of instructions. Its framework fits well in the typical workflow of an expert system 44, which involves the following steps (Forsythe & Hess 2001): a) collecting information from one or more human informants and/or from documentary sources. b) ordering that information into procedures (e.g., rules and constraints) relevant to the operations that the prospective system is intended to perform. c) designing or adapting a computer program to apply these rules and constraints in performing the desired operations.
So, one of the most important aspects of the formulation model is how entities are congregated to accomplish an efficient role in the formulation process.
What is then the role of the model’s entities? In urban space problems are complex and multifaceted. In general, a model built to respond to urban problems involves a great amount of entities45 (classes’s46 data) in intrinsic competition within the definition of its basic structure. The questions involving such a competition are diverse. One can set a trial question: If contradictory, is an urban rule (from an urban code) more or less important than a political measure to define a specification? At a first glance, it is
44 . ‘Expert systems are designed to emulate human expertise; they are constructed using computer languages that can represent and manipulate symbolic information. Each system is intended to automate decision-making processes normally undertaken by a given human ‘expert’ by capturing and coding in machine readable form the background knowledge and rules of thumb (‘heuristics’) used by the expert to make decisions in a particular subject area (‘domain’). This information is encoded in t he system’s ‘knowledge base’, which is then manipulated by the system’s ‘inference machine’, in order to reach conclusions related with the task at hand’(Forsythe & Hess 2001). 45 . In the urban context such entities (data classes and processes) covers a wide range of matters such as political visions, mandatory policies, participation actions (experts and communities), but they also comprise a data collection process, a cont extual analysis, and a design paradigm. 46 . Classes describe concepts in the domain.
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building a pre-design ontology: towards a model for urban programs
easy to suppose that such type of problems is out of the model. However, entities have to be positioned in the formulation structure so as its meaning enables the description of their precise role. If a role of an entity is not initially (or entirely) described, the formulation model has to frame it somehow. This means that classes and instances of information that are distributed and related with each other can impact the way the model functions. So, in a sense, the model entities are intrinsically the builders of their structure. But there are other difficulties. One is the range and diversity of the contextual data (rules, recommendations, existing population, existing morphology, culture, economy, strategies, etc.). The type of relations established among model entities changes according to the context. Such an unpredictability amplifies the difficulty to setup a closed chart of formulation rules. Therefore, theoretically, such a closed system is not viable because knowledge consists of a flexible structure to enable appropriate activities for specific problem demands. The conclusion is simple: knowledge acquisition and translation is often problematic (Forsythe & Hess 2001). This leads one to be faced with a problem. How to deal with model flexibility while, at the same time, data rules need to be encoded into a machine-usable form? It is important to a understand that formulation model entails a decision-making process of data acquisition and translation which calls for the use of a knowledge base model47 (KBS) here represented by a computational ontology48. Such a particular model provides the basis for dealing with the problems mentioned above, as explained in Chapter 3.
Then, how to create such an ontology? As mentioned in Chapter 3 there is no one correct way to build an ontology 49. An ontology is a formal explicit description of concepts in a domain of discourse, and its framework consists of a data modelling process within a problem-solving method that, in some measure, depends on assumptions of model’s manager (the formulation ontology engineer). Assumptions require a clean–up process of precision and accuracy. With precision, the non-
47 . An ontology together with a set of individual instances of classes constitutes a knowledge base. In reality, there is a fine line where the ontology ends and the knowledge base begins (Noy et al. 2000). 48 . Computational ontologies, in the way they evolved unavoidably mix together philosophical, cognitive, and linguistic aspects. Ignoring this intrinsic interdisciplinary nature makes them almost useless (Guarino 1998). 49 . An ontology defines a common vocabulary for researchers who need to share information in a domain. It includes machineinterpretable definitions of basic concepts in the domain and relations among them (Noy et al. 2000).
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building a pre-design ontology: towards a model for urban programs
intended models are excluded, and with accuracy 50 the negative examples are excluded (Guarino 1998). This means that capturing all intended entities, concepts, and models, is not sufficient to create a “perfect” ontology. To create an ontology, one has also to look at its application dominion. It is well known that cultural frameworks vary widely. Therefore, it is improbable that a sole model functions, properly, in a wide universe. This constraint demands for the establishment of a limit for the model’s applicability. For now one will consider the Western culture range. A complementary issue is the definition of territorial scale to which the ontological model can be applied. The site planning scale will be the application scale for the intended model.
Framing the ontology The first approach to the ontology is by means of cognitive domain knowledge and the domain of discourse, together with a definition of conceptual relations and ontology relations. Such an approach demands the creation of a conceptual diagram where main model classes are described. The diagram requires a formal structure of (a piece of) reality as perceived and organized by an agent, independently of the vocabulary used, and the actual occurrence of a specific situation, which is the base of an ontological conceptualization (Gruber 2005)51. The conceptual ontology52 shown in the next page was first developed to be presented at the eCAADe 2008 conference, and it corresponds to a domain of discourse or a conceptualization of the urban planning domain. The objective of the elaboration of the diagram was to organize the concepts and the relations that are established in a very initial phase of the planning process. Such phase corresponds to the pre-design phase, where the development and the management of an urban program occur. The developed ontology model is summarized in Diagram 16 (Montenegro, N. and Duarte J.P. 2008).
50 . When is a precise and accurate ontology useful? a)When subtle distinctions are important, b) When recognizing disagreement is important, c) When general abstractions are important, d) When careful explanation and justification of ontological commitment is important, e) When mutual understanding is more important than interoperability. 51 . Example of a conceptualization: A conceptualization for D is a tuple C = <D, W, ℜ>, where ℜ is a set of conceptual relations on <D, W>. A model for a language L with vocabulary V is a pair structure <S, I>, where S = <D, R> is a world structure and I: V→D∪R is the usual interpretation function. A model encodes a particular extension interpretation of the language. Analogously, we can encode an intension interpretation by means of a structure <C, ℑ>, where C = <D, W, ℜ> is a conceptualization and ℑ: V→D∪ℜ is an intension interpretation function. We call such a structure K=<C, ℑ> an ontological commitment for L. L commits to C by means of K. C is the underlying conceptualization of K (Guarino 1998). 52 . There is an ontology of the process (how is organized the pre-design phase?) and an ontology of the context and the product (description of the precise context of the urban space, its regulations, its sorted data, and the description of a series of solutions, and guidance).
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building a pre-design ontology: towards a model for urban programs
16. The urban formulation ontology (Montenegro, N. and Duarte, J, 2008)
Now, the description of the diagram The diagram is organized in two distinct parts: a) the pre-design phase 1, and b) the pre-design phase 2.
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building a pre-design ontology: towards a model for urban programs
In general, in the pre-design phase 1 (PD1) site and population are analysed, as well as general strategies and constraints imposed on the territory. PD1 corresponds to the input data of the basic conceptual model. In the end of this first phase, a document 53 will synthesise all collected data enabling its use in the second phase of the pre-design process. Then, in the predesign phase 2 (PD2), data is codified towards the creation of specifications for urban design. Such specifications correspond, in summary, to the urban program. The output of PD2 is, therefore, the output of the basic conceptual model. The diagram depicts the different phases of the formulation process, the type of data manipulated, and the participants involved. In the gray boxes positioned in the bottom of the diagram are located the crucial components of the formulation model. These elements encompass core categories of the model that correspond to diverse functions or tasks. Their related elements are disposed in a vertical line within the diagram, as the example described below; to the component â&#x20AC;&#x153;stagesâ&#x20AC;? corresponds two different vertical entities: 1. pre-design phase 1, and 2. pre-design phase 2.
This vertical reading dominates over other elements. Overlaid on the described vertical dominant line co-exists a horizontal reading. Considering the example above, the pre-design phase 2 is one of the stages of the overall pre-design phase that includes two types of planning actions/themes: 1. the language, and then to 2. the design patterns.
While the vertical line represents the thematic domains of the formulation process drawn in chronologic order, the horizontal line embodies a scale decomposition of the necessary subjects essential to produce an urban program. Both vertical and horizontal readings are complementary.
53 . The Document Synthesis (DS).
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building a pre-design ontology: towards a model for urban programs
To facilitate the understanding of the diagram, a set of additional representation aids, such as arrows and small gray titles, were located among diagram entities to qualify and clarify their roles in the process (role representation). Moreover, the way arrows are pointing indicates the action flow that usually occurs between adjacent entities.
Sketching the ontology of the formulation process
Although the structure of Diagram 16 seems clear, it is not entirely precise. The relations established among PD classes and instances do not correspond to the result of a computational ontology. On the contrary, the structure of the diagram corresponds to a conceptual sketch (or a conceptual discourse of the urban domain) to feed the final ontologybuilding. By computing an ontology (using an ontology editor like Protégé), one can assure a high level of accuracy of the developed model. Such precision drifts from the embedded rules of the editor that constrain how ontological objects are linked and impose implicit conventions on their relational status. At the same time, such edition maintains a hierarchical order within model classes54. It is important to mention that, in future research the diagram components will be encoded into such a knowledge modelling structure (a computational ontology) to enable the description of implicit rules in an explicit way. This means that it is important to establish instances within the model classes in order to portray value and partnership, defining if an element or entity is part of another one, or if an entity interacts with another one in some way, or even what an entity “is” following the description of “what is”. The diagram 17 shows the sketch of an edition built in the Protégé-Frames editor in accordance with the Open Knowledge Base Connectivity protocol (OKBC). The ontology describes PDP (dark green box), PD1, and PD2 (light green boxes) superclasses, between context and final specifications slots.
54 . The descriptions of such methodology are defined in the third chapter of this research.
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building a pre-design ontology: towards a model for urban programs
17. PD classes, subclass-superclass hierarchy, slots and instances (in light blue). Bellow the ProtĂŠgĂŠ VizTab
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building a pre-design ontology: towards a model for urban programs
04 • basic conceptual model • formulation model
The objectives of the fourth chapter are: a) the description of the basic conceptual model, and b) the description of the three parts of the formulation model: b1) the input, b2) the mechanism, and b3) the output.
The basic conceptual model consists of three basic components that represent the three basic functions of the model as shown in Diagram 18: 1) 2) 3)
the Input (to read contextual data), the Interpreter (to interpreter received data), and the Output (to describe specifications for design).
data path
INTERPRETER •design specifications
•contextual data
•machine
INPUTS
OUTPUTS
data path
18. Urban formulation process (FMo)
The formulation model (FMo) is the detailed structure of the conceptual model as shown in the ontological Diagram 12 of this research.
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building a pre-design ontology: towards a model for urban programs
The contribution of the fifth chapter for this research is to describe the formulation process as well as the design phase where it occurs â&#x20AC;&#x201C; the predesign phase. The main objective is to provide a better understanding of the formulation framework and, at the same time, to generate the sketch of its semantic ground, that is, a consensual vocabulary
to
enable
appropriate
specifications or the â&#x20AC;&#x153;communication actsâ&#x20AC;? towards design solutions.
Chapter 5 5. The Formulation Process
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building a pre-design ontology: towards a model for urban programs
5.1. Introduction
The contribution of the fifth chapter of this research is to describe the formulation process as well as the design phase where it occurs – the pre-design phase. The main objective is to provide a better understanding of the formulation framework and, at the same time, to generate the sketch of its semantic ground, that is, a consensual vocabulary to enable appropriate specifications (or the “communication acts” (Gandon 2002)) towards design solutions. The formulation process corresponds to a specific phase of the design process called pre-design phase. In short, the pre-design phase consists in a phase of analysis and interpretation of data that occurs before design begins (Best & De Valence 1999). Usually, during this phase, studies are done to analyze the context and identify the requirements, constraints, and opportunities for a given site (McCallum et al. 1996). In general, it also consists of a set of guidelines to assist planner’s actions.
5.2. Operational structure of the formulation process
The relevance of the pre-design phase becomes apparent when placed in a project scheduling diagram. PD phase represents about
of the overall design process varying in significance
throughout different stages55 (Best & De Valence 1999). PD represents the query phase of the design process, and its main objective is to facilitate the definition of strategies towards design solutions. To understand more clearly the purpose of the formulation model it is essential to observe its different stages. All starts with a contract that corresponds to an agreement between two parties frequently a promoter and a design team. These parties, governed by particular interests, configure a team searching for specified goals (occasionally dissimilar). The possible existence of different visions among different parties requires an effort of convergence to benefit the
55 . In fact, the planning process can be present during all design process mainly because it deals with permanent factors such as collaboration, and participation.
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building a pre-design ontology: towards a model for urban programs
end result.
The success of a collaborative environment is therefore crucial for the
accomplishment of formulation goals (Mabert et al. 2003). Following the contractual agreement, the process usually continues with a definition of a schedule to implement the necessary steps required for generating the plan. It is important to mention that the pre-design process frequently extends to the schematic design phase (SDP) (Alexander et al. 1987) - the phase that follows the pre-design phase. This happens because it is essential to monitor the development of this early and conceptual phase of the design process. This means that the formulation process 56 corresponds more to an extended course of action rather than a locked process (Huberman & Miles 1994). Diagram 19 describes a summary of the conventional main actions of the design process.
19. A planning schedule57
56 . It is also usually called as the programming phase (or framework) of the design process. 57 . The Bid phase described in the schedule corresponds at the following concept: Design-bid-build (or design/bid/build, and abbreviated D-B-B or D/B/B accordingly), also known as Design-tender (or "design/tender"), is a project delivery method in which the agency or owner contracts with separate entities for each the design and construction of a project. Design-bid-build is the traditional method for project delivery and differs in several substantial aspects from design-build. There are three main sequential phases to the design-bid-build delivery method: 1. The design phase, 2. The bidding (or tender) phase, and 3. The construction phase.
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building a pre-design ontology: towards a model for urban programs
5.3. The formulation phases It seems that the formulation process includes two different main phases: a) pre-design phase 1 (PD1) and b) pre-design phase 2 (PD2).
How and why such phases are subdivided from the generic pre-design phase? In general, the division into different parts writes to a method of simplification. The main idea behind this method is - divide a problem (PDP) into sub-problems (PD1 and PD2) of the same type58 to simplify and explicit the problem domain. As a computer programming technique this is called divide and conquer (dialecting59), and it is key to the design of many important algorithms, as well as a fundamental part of dynamic programming. The division of the formulation process into different parts (here represented by its phases) has an additional logic - it corresponds at two different conceptual sub-dominions of the formulation framework, as is shown in the diagram 16; a) A data acquisition phase (that occurs in the PD1) and, b) A data translation phase (that occurs in the PD2).
Data acquisition corresponds to a phase where contextual data (site and population as well as strategies politically framed and existing regulations) are acquired (Kay 1984). This phase is crucial to identify the essential ingredients that will constitute the formulation database. Data translation corresponds to the creation of the set of specifications to describe a solution (or a set of solutions) by applying rules that link contextual data to programmatic features, that is, the translation of the contextual data (from the formulation database) into design specifications. The idea is to build-up such specifications under the form of patterns
58 . Such type of division will be implemented throughout all formulation process where divided parts will describe sub -classes of super-classes of the overall process (here refer to as an ontology). 59 . Dialects are domain specific sub-languages of a programming language or a data exchange language. (See also Grammaroriented programming, Language oriented programming, Reflection and Metaprogramming.) A language supporting this paradigm encourages users to create new dialects for specific problematic domains.
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building a pre-design ontology: towards a model for urban programs
according to Alexander’s formalities (Alexander 1979). The rules are inferred a priori for a general context, say, Portuguese urban environments, and then applied to a specific context, that is, a specific site and its surroundings. The ultimate goal of this research is to infer such rules. In this chapter, it will be presented, when necessary, a simplified version of the ontological Diagram 16 to explicit the main phases and processes of the formulation framework. In the first simplified diagram reproduces below are highlighted (in black text) the different phases of the pre-design phase – the PD1 (data acquisition) and the PD2 (data translation).
PD2 data translation
strategic plans urban codes and guidelines
pattern language 'specifications for design'
site and population context
design (solution)
context (problem)
PD1 data acquisition
20. Pre-design phases – the PD1 (data acquisition) and the PD2 (data translation)
5.4. Categories enclosing the main processes of the pre-design phase The categories shown in Diagram 21 are to ontological super-classes that correspond to two information acquisition and processing phases that occur during the formulation process; in the first phase the goal is to analyze the context (PD1), in the second phase (PD2) it is to develop specifications to guide the planner’s design process. There is a conventional hierarchy in the use of that information. Normally, in the PD1, the first required data (that will guide and constraint the other categories of information) is composed by the set of political strategies defined for a territory under study (I). The second data category usually includes urban regulations that are
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building a pre-design ontology: towards a model for urban programs
applicable to the intervention site (II), and the third one is a portrait of the site and population (III). In the second phase (PD2) there is only one category group that is used to translate the PD1 database into a set of specifications encoded as urban patterns (IV). Despite the description above, the hierarchy of the described categories can changed according to specific demands of the problem (such as particular procedures undertaken, involved parties, or strategic procedural recommendations, etc.).
strategic plans (I) urban codes and guidelines (II)
PD2 data translation pattern language 'specifications for design' (IV)
site and population context (III)
design (solution)
context (problem)
PD1 data acquisition
21. The four categories of the formulation process
Now, a closer look at each one of the categories, starting by the formulation strategies.
5.5.
Strategies Strategies consist of the first category of the pre-design phase 1 (PD1) and are related with high level decisions that are usually taken even before the intention of producing a particular plan is completed. Strategies are crucial in the implementation of urban programs because they represent a crucial benchmark towards sustainable development. The outcome of an urban design process is an urban plan. So, in urban design the resulting design is delivered in the form of a plan, and one of the top requirements for urban plans is the definition of a strategy, to identify the main purposes of the plan (Ulrich & Eppinger 2003).
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building a pre-design ontology: towards a model for urban programs
How to manage strategy in the ontology? The flow between strategies and design can collapse if strategies reveal insufficiency, ambiguity, or inaccuracy within its conceptualizations (Gruber 1991). The creation of a computational ontology helps to surpass this difficulty as its main goal is to disambiguate 60 by means of an inference61 machine that attains at data consistency (Caneparo et al. 2007). Therefore, there is a clear advantage in the use of a knowledge modelling62 structure (in this case an ontology) to frame a planâ&#x20AC;&#x2122;s strategies. Above all, an ontology can avoid ambiguities within design outcomes and, at the same time, it can reinforce its accuracy. The chain seems to be clear. Designs well supported by precise and proficient strategies (or development visions) lead to better plans. What are the subject matters behind a planâ&#x20AC;&#x2122;s strategies? Strategies are framed by political visions supported by national and regional policies established for territories (Graham & Marvin 2001a). The economic, the cultural, and the social foci in urban communities correspond to core components of such policies (Herrschel & P. Newman 2002b). These policies are difficult to capture in the formulation database model. The main reason for such difficulty stems from the variable character of policy which changes according to the nature of the administration. Political parties hold particular conceptions about governance and management of spatial resources. This has a direct influence on the definition of urban programs and thus on plans. Strategies also work at different scales. In abstraction, strategies may start with policies endorsed to vast regions and may end in rules or
60 . In computational linguistics, word sense disambiguation (WSD) is an open problem of natural language processing, which comprises the process of identifying which sense of a word (i.e. meaning) is used in any given sentence, when the word has a number of distinct senses (polysemy). The solution of this problem impacts other tasks of computation linguistics, such as discourse, improving relevance of search engines, anaphora resolution, coherence, inference, and others. Research has progressed steadily to the point where WSD systems achieve consistent levels of accuracy on a variety of word ty pes and ambiguities. A rich variety of techniques have been researched, from dictionary-based methods that use the knowledge encoded in lexical resources, to supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, to completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date (Navigli & Velardi 2005). 61 . Inference is the process of drawing a conclusion by applying rules (of logic, statistics etc.) to observations or hypothesis; or by interpolating the next logical step in an intuited pattern. The conclusion drawn is also called an inference. 62 . Knowledge management (KM) comprises a range of strategies and practices used in an organization to identify, create, represent, distribute, and enable adoption of insights and experiences. Such insights and experiences comprise knowledge, either embodied in individuals or embedded in organizational processes or practice. An established discipline since 1991 (see Nonaka 1991), KM includes courses taught in the fields of business administration, information systems, management, and library and information sciences (Alavi & Leidner 1999). More recently, other fields have started contributing to KM research; these include information and media, computer science, public health, and public policy.
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building a pre-design ontology: towards a model for urban programs
recommendations at the urban site scale covering a wide spectrum of influence. At site scale, strategy represents the very initial step towards the implementation of the plan. However site strategies also entail a higher sphere of decision that usually defines a development path for a wider region (Evans et al. 2007). Such path focuses on a site within a region (a “part” within “whole”). The purpose is to obtain a territory balance surpassing the neighbourhood scale range (J. C. Moughtin et al. 2003). When this process starts? An important aspect concerning planning actions is related with the necessity of defining a plan’s strategy before planers start their design conceptions. Planners have to consider the demands of the strategy to fit the design into the strategy’s goals. What is the role of planners in this process? If one states the problem in a plain and rhetorical way, on one side of the formulation process stands the promoter, public or private, with a particular set of goals and, on the other side, complementarily, stands the planer with its particular design approach. The first has the responsibility to conceive the macro strategy and the general confinements for the plan. The second has to collect data from the defined strategy and the plan’s confinements to transform it into spatial solutions, supporting these on design guidelines. However, the involvement of planners in the development of plans varies according to the context. Planners are usually skilled to participate throughout the formulation of the program and in the creation of designs. However, they also can participate in the elaboration of strategic plans contributing within an ample participative process (Graham & Marvin 2001b). How to elaborate a strategy? One can say there is no universal formula to define a strategy.
The existing
methodologies are varied, however, the instruments that regulate the elaboration of strategic plans are relatively well known. What is then a strategic plan? A strategic urban plan63 (SUP) is a planning instrument that holds in its framework a wide number of subjects to inquire (McCallum et al. 1996). Such variety requires the use of a multiplicity of methodologies and tools to identify and clarify the subjects focused on
63 . A strategic plan lets an organization know where they are now and where they want to be some time in the future.
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building a pre-design ontology: towards a model for urban programs
population and site features (Healey 1997). At the core of the strategic outline are placed the economic, the cultural, the social and the political features, frequently identified using tools like SWOT (Strengths, Weaknesses, Opportunities, Threats) depicted in Diagram 22, and PEST (Political, Economic, Social, and Technological analysis) methods. In addition, other tools may be use to deal with complementary matters such as “PERS (Pedestrian Environment Review System) by TRL Software (http://www.trlsoftware.co.uk/: May 2008) or “Design Quality Analyser” by CABE (http://www.whichplaceswork.org.uk/: May 2008)”, (Gil 2008) amongst others. Despite its relevance. SUP methods are not generalized in urban design processes yet.
22. SWOT analysis - the strengths, the weaknesses, the opportunities, and the threats.
SUP is today considered a type of Governance. According to Borja and Castells (1998), “the definition of a city project that unifies diagnoses specifies public and private actions and establishes a coherent mobilization framework for the cooperation of urban social actors. A participative process is a priority when defining contents, as this process will be the basis for the viability of the objectives and actions proposed. The result of the Strategic plan should not necessarily be the creation of regulations or a government program (although its adoption by the State and Local Government should mean the instigation of regulations, investment, administrative measures, policy initiatives, etc.) but rather a policy contract between public institutions and civil society.” What are SUP’s assessment instruments and methodology? Strategic plans are framed by specific frameworks towards the definition of a plan’s purposes (Mintzberg 2000b). Usually they consist of the following five main concepts:
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building a pre-design ontology: towards a model for urban programs
1) Vision – to define the vision / to set a mission statement with a hierarchy of goals; 2) SWOT – to analyse according to the desired goals; 3) Formulate64 - to prepare actions and processes that can be taken to attain these goals; 4) Implement – to implement of the agreed upon processes; and 5) Control – to monitor and get feedback from implemented processes to fully control the SUP operation. There are a number of ways to develop SUP’s but typically a three-step process may be used to support the development of the mentioned concepts above (Mason & Mitroff 1981): 1) Situation – to evaluate the current situation and how it came about, 2) Target – to define goals and/or objectives (sometimes called ideal state), 3) Path – to map a possible route from the goals to the objectives. One alternative approach is called Draw-See-Think; 1) Draw – where the key question is: what represents the ideal image or the desired end state? 2) See – setting the relevance of observing reality: what is today's situation? What is the gap from ideal and why? 3) Think – defining a prospective path: what specific actions must be taken to close the gap between today's situation and the ideal state? 4) Plan – and finally, how to make it: what resources are required to execute the activities? An alternative to the Draw-See-Think approach is called See-Think-Draw; 1) See - what is today's situation? 2) Think - define goals, 3) Draw - map a route to achieving the goals.
The diagram 23 depicts strategies as the initial phase of the pre-design process (PD1). Moreover an example of SWOT and PEST tables is presented in Annex 3.
64 . Formulate corresponds here to a precise term used in SUP theory.
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building a pre-design ontology: towards a model for urban programs
context (problem)
strategic plans (I)
urban codes and guidelines
(II) site and population context
PD2 data translation pattern language 'specifications for design'
(IV)
design (solution)
PD1 data acquisition
(III) 23. Strategies shown in the simplified diagram (highlighted in black text and box).
5.6. Regulations
Now, a closer look at the description of the second category of the formulation model regulations. In summary, regulations consist of a compilation of urban rules, codes, standards, and sorted requirements (Carmona et al. 2006). An important aspect related to its nature is the width of its application. Such aspect set a difficulty. Urban rules generally differ from country to country, and from site to site within particular geographic locations. In fact, this variation can be extended to the universe of cultural contexts which comprise an infinity of variables. To solve width and differentiation one can search for agreed upon rules applied to vast regions of the globe as the regulations applied to the European Union (EU). However the dilemma remains. The EU is just a part of a wider universe of urban realities and cultures, and additionally its administration largely lacks the legal means to enforce regulations. This occurs since the â&#x20AC;&#x153;EU policy is mainly focused on structural policies to regulate international trade and economic markets, employment, and industry sectorsâ&#x20AC;? (Hix 1999). How rules are defined? Rules usually depend on policy within state administrations, however social involvement of communities in the definition of specific constraints or rules for plans, can add performance into plans by adequating designs to communityâ&#x20AC;&#x2122;s particularities (Harvey 2009). Such
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community participation generally occurs during the SUP framework or following it, in the definition of the planâ&#x20AC;&#x2122;s final layout. However, it can also occur in other phases of the predesign framework as in the definition of urban rules to apply in the development of particular plans. Meanwhile one can argue that such processes involve several formalities and nuisances. For now it will be just acknowledged the relevance of such a participation process. Who should be involved in such a participation process? In fact, all society can be involved in participation but some civil sectors seem to receive more direct benefits with the application of regulations or design-codes than others. Thus they are able to contribute with additional knowledge that can bring benefits to plans requirements as a result of their particular visions and experiences. Traditionally such sectors are composed by landowners, developers, local authorities, as the community in general (represented by individuals or a committee) (Evans et al. 2007). Table 1 shows the mentioned participants and the roles that they play in the formulation framework.
1.
Benefits of design regulations (Evans et al. 2007)
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In future research it will be elaborated a catalogue of regulations within a case-study. The objective is to create a consensual directory of standards. Such directory will represent a particular universe giving the prototype model of the formulation process some accuracy. Such directory will be organized into modules that can be retrieved and manipulated by planners to inform the development of a particular plan. In general the directory will contain a sort of regulatory controls (includes on-site and off-site considerations) such as: a) LRDP land-use designation, b) urban codes and requirements, c) precinct or area plans, d) site zoning and surrounding area zoning, e) existing land-use type and density, f)
permitted uses and exemptions,
g) deed restrictions and covenants, h) setbacks (lot coverage, and height limitations), i)
parking requirements, and
j)
signage requirements.
The diagram 24 shows the regulationâ&#x20AC;&#x2122;s box that follows the strategies box in PD1. In Annex 4 are presented some core attributes, which are usually necessary to apply regulations.
PD1 data acquisition
PD2 data translation
(I) urban codes and guidelines (II) site and population context
pattern language 'specifications for design'
(IV)
design (solution)
context (problem)
strategic plans
(III) 24. Regulations and codes shown in the simplified diagram (highlighted in black text and box)
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5.7. Site and population context Site and population data is normally acquired during (or as sequence of) the strategic phase (Rogers & Vertovec 1995). In such a phase, if the SUP defines, for example, a specific goal towards the increasing of social cohesion within a plan. A planner may also want to extend or transform SUP defined goals to respond to other needs of the plan. In this case is important to maintain a high level of flexibility within the formulation model so that management of the formulation database (by planners) can be made in a flexible and extensive way. The selection of such data is basically built on: i) population statistics, and ii) site analysis (sub-divided into ii1, ii2, ii3, and ii4).
Now, let us take a closer look at each of the data groups.
i) Population statistics A relevant part of population data can be directly gathered from national and international statistical institutes, (UNESCO) 2009; Balachandran 1980) which generally provides for vast amounts of information related to people. Usually such information supports communityâ&#x20AC;&#x2122;s characteristics where profiles are ordered by age, ranges, skills, professions, genders, economic stratification, etc. This information is frequently well supported by relational 65 diagrams that help the visualization of data correlation66. Data correlation can be managed by the organization of features into charts in order to express specific values that can be divided by timeline periods. These diagrams portray global tendencies (Chenery & Taylor 1968)(Montgomery 2008) to define or correct planning streams.
65 . A relational database matches data by using common characteristics found within the data set. The resulting groups of data are organized and are much easier for people to understand. 66 . A correlation function is the correlation between random variables at two different points in space or time, usually as a function of the spatial or temporal distance between the points. If one considers the correlation function between random variables representing the same quantity measured at two different points then this is often referred to as an autocorrelation function being made up of autocorrelations. Correlation functions of different random variables are s ometimes called cross correlation functions to emphasize that different variables are being considered and because they are made up of cross correlations. Correlation functions are a useful indicator of dependencies as a function of distance in time or space, and they can be used to assess the distance required between sample points for the values to be effectively uncorrelated. In addition, they can form the basis of rules for interpolating values at points for which there are observations.
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Population represents a crucial factor towards the definition of a plan which is quite simple to explain. Urban space is designed by people and for people. Communities are the main purpose and the main constraint of a plan - its first ingredient. Therefore population characteristics determine and deeply influence spatial configurations. ii) Site analysis67 Site analysis is the second top group of contextual data, which consists of a crucial task of the pre-design process implying spatial perception (Pereira 1996). Such a relevance is easy to depict. Space is perceived, apprehended, and seized by humans. Lynch (1960) wrote that users understood their surroundings in consistent and predictable ways by forming mental maps. By providing a framework to take this world of visual and formal perception into account, Lynch’s “The Image of the City” has had important and durable influence on the field of urban planning. Today’s methods of site analysis, deeply embedded in Lynch’s principles, are elaborated through a collection of visual annotations, and interpreted through simple statistical charts. Nevertheless, such a process reveals a variety of flaws due to cognitive constraints on the behalf of the observer. Site analysis is also extensive. To explicit its different implications and methods one presents a partition within four types of site analysis. The first is based on a method to read the image of an urban area (Pereira 1996), as described in following.
ii.1) Site Analysis (The image of the city) According to Pereira (Pereira n.d.), the analysis an urban area needs to take into account: 1) a global interpretation, 2) the problems and potentials, 3) the urban character, 4) the dynamics of transformation, and
67 . The analysis phase is a chronological step of the design process. This step involves programming the site as well as site and user analysis, which is focused on in-depth below. There are numerous site elements related to the analysis during this phase.
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5) the objectives, the politics, the strategies, the solutions, and intervention actions. Such site scrutiny requires a methodology of implementation, that is; a) the preparation of a technical team, b) the organization of its actions, and c) the compilation of assessment studies. In general, this type of analysis starts from the description of the urban context (Rogers & Vertovec 1995), namely through the description of its morphology, the stages of its historical evolution and urban demography, its social-economic growth, its accessibilities, its general distribution of population and land uses, its landmarks (centrality, historical, and touristic), its planning strategies, and its urbanization plans and public works (existing or approved, its constrains and commitments). Its fieldwork68 usually involves the use of cartography and photography, toponymic analysis, street interviews and registration of opinions through blogs, sites or other media, noise levels registration (in the case of an absence of noise-charts these data are registered directly on site), etc. The use of complementary studies also helps on data collection in matters such as landscape morphology (plateaus, lines of the landscape, slopes, three-dimensional representation of land), urban historical evolution (the stages of urban formation, the demassification and growth of the urban structure), social patterns, ideals and the models of city, social-economic characterization of the population (age, composition of the families, activities), neighbourhood relationships, as well as the forms of access to the interior of the urban site under study. The physical and visual inspection of the site is considered a crucial step in this type of urban analyses. There are several aspects that need to be taken into account in the analyses, namely; 1) the recognition of approach pathways, 2) the definition of the site peripheral edge, 3) the recognition of connections with the surroundings,
68 . Field work is a general descriptive term for the collection of raw data. The term is mainly used in natural and social sciences studies. It is more technically known to scientific methodologists as field research. Field work, which is conducted in situ, can be contrasted with laboratory or experimental research which is conducted in a quasi-controlled environment.
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4) the morphologic continuities and discontinuities, and 5) the observation of distant focal points. Such analysis follows the elaboration of a chart list (Pereira 1996) that can be described as follows: a - Site Data a1 Morpho-typological structure: a1.1 Land form and features (topography: slope and aspect). a1.2 The formation bases of the urban structure (site morphology and historical evolution), a1.3 Land use (general indicators of land use), a1.4 Urban mesh (grids and their orientation, mesh geometry, public spaces network), a1.5 Urban space (public space, private space and semi-public space), a1.6 Built space (building construction dates, types of construction, current and state of conservation, typologies, patrimony, delimitation of rundown areas, costs, regeneration strategies). a2 Active structure: Activities during the day, night and weekends: a2.1 Housing, equipment, public administration and economic activities, a2.2 Transportation, parking, loading docks and circulations, a2.3 Leisure, culture and exchanges. a3 Social structure: a3.1 Characteristics of the population: Socio-economic, age and ethnic groups69, a4 Significant structure: a4.1 System of orientation, a4.2 Axes, a4.3 Focal points, a4.4 Passages, a4.5 Reference areas,
69 . a) 3.1 can overlap with content in i), population statistics. One of the tasks of the ProtĂŠgĂŠ 2000 Editor is to clean up such type of occurrences in order to prevent ambiguities.
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a4.6 Tourist routes. b - Urban furniture and symbols, plant and animal species: b1 Illumination, b2 Culture and leisure, b3 Information and orientation, b4 Services to the community, b5 Security, b6 Vegetal and animal species. c - Urban character: c1 Sequences of public spaces, c2 Sequences of faรงades, c3 Significant details, c4 Pallet of colors, c5 Human environment, c6 Environment of the installed activities and circulation, c7 Sound and light environment, c8 Vegetation and landscape. d - Urban Dynamics: d1 Modernity or traditionalism of the activities, d2 Socio-economic contrasts. e - Climate: e1 Prevailing winds (direction and velocity), e2 Solar orientation (including shade and shadows), e3 Temperature ranges and seasonal norms, e4 Humidity, e5 Precipitation. f - Environmental influences: f1 Noise levels, f2 Odors, f3 Fumes, f4 Dust, f5 Smoke from adjacent sites,
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f6 Air quality, f7 Vibration, and f8 General nuisances.
ii.2) Site Analysis (Data Mining) Data mining comprise a very specific type of site analysis related with the use of technology. The relevance of its methodology and specificity calls for its description. What is then Data Mining? A data mining (DM) process is “characterized by a recursive withdrawal procedure enthused by a statistical platform towards data emergence, and is commonly used to perform three main tasks” (Fayyad et al. 1996): 1) Classification - arranging the data into predefined groups, 2) Clustering - where the groups are not predefined and the algorithm tries to group similar items together, and 3) Regression - to find a function which models the data with the least error. Technically data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. The relevance of these techniques to the planning process is that they allow users to analyse data from different angles, categorise, and summarise the relationships identified. Data mining seems to facilitate the discovery of patterns that would be difficult to reveal in a complex urban space, today controlled by a bursting environment of economic and social phenomena.
ii.3) Site Analysis (Space Syntax and other methodologies - Hillier, 1984) This group embraces another important chapter in spatial analysis. Space syntax is based on linear representations of space (desire lines theory) through definitions of lines and segments (axial mapping methodology). One of the methodologies used by space syntax (SpS) is characterized by network measurement through graphs representations. The results of the applied theory seem to provide accurate results that are essentially focused on social and traffic assessment. The aphorism of the space syntax (Bafna 2003) is based on visual space perception and physical space recognition; “to see how much
we can learn about (…) surroundings without taking into account intent” , defining as main subjects under study; “moving people, bicycles or vehicles”. The method usually encloses a
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number of street locations covering a range of well-used, moderately-used and poorly-used spaces, in and around a defined area of study. SpS methodology identifies a set of “gate” positions. “The more gates, the more accurate the picture of movement patterns” (Batty 2004). Finally, it defines a simple procedure, by “stand at each gate position and draw an imaginary line crossing the street space (the line should be at a right angle to the direction of the street) (see map and observation sheet 2). Those gates are spots where one will count the people or vehicles that cross this line for a set period of time. Some of the instructions are; “Count only the people or vehicles that have crossed the line. The time periods vary from 2.5, 5 to 7.5 minutes depending on the busyness of the area: shorter times for busy areas and longer times for quieter areas. The time period should be as precise as possible down to the nearest second. Always record the time period. This is so that when times are multiplied up to arrive at rates per hour no mistakes are made” (Hillier et al. 1976).
2.
Gate Counter Map and Observation sheet example.
ii.4) Site Analysis (Measuring quality) The last group of site analysis is focused on quality standards. It states that “measuring quality means involving a variety of interested people to define how well a space works. Through this process one can learn about requirements of different groups of people to understand if their needs are being met. It will identify both good and bad characteristics and stimulate new ideas for improvements and how it could be managed” (Dempsey 2008). This process will help to
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develop good relations between users and people who run space and will help one prioritise improvement. By measuring quality70 one is basing such decisions on good evidence. In summary the existing tools for measuring quality can be used for: a) identifying the strengths and weaknesses of a space, b) establishing what is most important to people, c) comparing different people’s views, d) measuring how well the space meets everyone’s needs, e) stimulating new ideas for improvements, f) tracking changes in people’s views over time, g) bringing staff and users together in a structured way to discuss the space (Hurley et al.)
The use of Site Analysis within the formulation model.
The techniques used in SUP’s and in the site analysis phase, involving this type of information, can be similar despite the different moments in which they occur during the pre-design phase. The question concerning the necessity of covering twice the same problems using similar methodologies (in SUP and in the Site Analysis) needs to be addressed by the participants of the plan that should decide if the sources of the SUP are sufficient or even if they should be presented taking into account the specific requirements of the design and pre-design phase. Finally, the diagram 25 represents the site and population contextual data acquisition as the last process of the pre-design phase 1 (PD1). Once more it can be mentioned that order of the processes described in the diagram can be structured differently, according to the plan’s specificity.
70 . A quality (from Latin qualitas) is an attribute or a property. Attributes are ascribable, by a subject, whereas properties are possessible. Some philosophers assert that a quality cannot be defined. In contemporary philosophy, the idea of qualities, and especially, how to distinguish certain kinds of qualities from one another remains controversial (Thomson et al. 2003).
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PD1 data acquisition
PD2 data translation
(I) urban codes and guidelines
(II)
pattern language 'specifications for design'
site and population context (III)
(IV)
design (solution)
context (problem)
strategic plans
25. Site and population contextual data shown in the simplified diagram (highlighted in black text and box)
5.8. Document synthesis There is too much information for analysis? The wide-range of matters under analysis seems to be endless, sometimes confusing and frequently overlapping. Such extended data is difficult to understand in order to organize and select. The task is especially hard when such information is manipulated by several parties with different visions about its management. The data from the analysis phase is useful for the planâ&#x20AC;&#x2122;s stakeholders only when inclusive, limited and precise. Though is crucial to have the perception of what to do with it.
So, how to deal with such an amount of information? In this phase, it is essential to elaborate a final document to summarize all the compiled data. This document is usually called synthesis document (SD) and its structure is defined by: a) objectives, guidelines and strategies, as well as b) a formulation of hypotheses towards implementation. Pereira (1996) recommends a set of five instructions to define SDâ&#x20AC;&#x2122;s. a) the first describes the need to elaborate general cost estimates and execution phases for the plan, b) the second defines all formulation rules for implementation on site, c) the third defines the financial resources required to implement the plan, d) the fourth identifies the social participants involved in such implementation, and
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e) the fifth develops a series of public discussions through media (meetings, blogs, etc.). What are the data attributes? It is difficult to describe with precision what represents (in a moment) each contextual entity because it changes according to the plan’s requirements. However, is possible to describe a relatively consensual database of their related attributes71. Annex 4 provides a list of attributes related to contextual data, including their proposed codes, the description of their types, their reference values, their data sources, and also their related calculations. The tables express a set of attributes usually used in Buildings, Blocks, Plots, and Streets configurations. Such tables were developed as the database for data-mining research (Gil et al 2009).
5.9. Planner’s Language – pattern language
This category of the formulation process is located in the second phase of the pre-design process – the PD2, and it is essentially related with the description of design specifications. A first question arises immediately concerning this topic. The development of the formulation database seems to reduce the role of planners in decision making concerning the planning actions. In contrast, planners are crucial elements in the management of the formulation model, as they can also act as its system engineers (the administrators of the formulation ontology and its rule based system). The idea is that some balance can be made. Another important role of planners is to achieve consensus amongst stakeholders by harmonizing different visions regarding a site. Consensus is hard to manage specially before the wideness of participants possessing dissimilar interests. Table 3 and 4 gives one a notion concerning stakeholder’s roles, as well as their short-term value/ long-term value within a plan’s development. This management consists, largely, of a planner’s language the planner’s communication acts.
71 . The word ‘attribute’ can express: in philosophy - property, an abstraction of a characteristic of an entity or substance; in social sciences - a characteristic of a variable; in linguistics - a syntax unit, either a word, phrase or clause, that modifies a noun; in computing - attribute (computing), a factor of an object or other kind of entity.
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3.
Participants in the planning process (Evans et al. 2007) â&#x20AC;&#x201C; part 1
4.
Participants in the planning process (Evans et al. 2007) â&#x20AC;&#x201C; part 2
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During the second pre-design phase planners are called to produce the largest part of their work before starting the design of a plan. It is a complex activity involving different knowledge domains, some linked to personal assumptions72. Planners communicate their ideas by a sort of language, a planning language composed by; a) a particular lexicon 73 (built of patterns), b) a specific organization (syntax74), congregating a c) group of intentions (a semantic corpus). This language will determine the structure of the design specifications.
Diagram 26 shows the location of the planning language box (the planner´s pattern language) in the overall pre-design process - phase 2 (PD2). This process is further described in the Chapter 6.
PD1 data acquisition
PD2 data translation
(I) urban codes and guidelines
(II) site and population context
pattern language 'specifications for design' (IV)
design (solution)
context (problem)
strategic plans
(III) 26. Pattern language “specifications for design” shown in the simplified diagram (highlighted in black text and box)
72 . An assumption is a proposition that is taken for granted, as if it were true based upon presupposition without preponderance of the facts. Assumption may also refer to: in logic, natural deduction systems are defined as an assumption is made in the expectation that it will be discharged in due course via a separate argument; in mathematical modeling it can be used to map the outcome of different assumptions on the system being modeled. 73 . In linguistics, the lexicon (from the Greek: Λεξικόν) of a language is its vocabulary, including its words and expressions. More formally, it is a language's inventory of lexemes (Podgorski 2008). 74 . In linguistics, syntax (from Ancient Greek σφνταξις "arrangement" from σφν syn, "together", and τάξις táxis, "an ordering") is the study of the principles and rules for constructing sentences in natural languages. In addition to referring to the disc ipline, the term syntax is also used to refer directly to the rules and principles that govern the sentence structure of any individual l anguage, as in "the syntax of Modern Irish. Modern research in syntax attempts to describe languages in terms of such r ules. Many professionals in this discipline attempt to find general rules that apply to all natural languages. The term syntax is also s ometimes used to refer to the rules governing the behavior of mathematical systems, such as logic, artificial formal languages, and computer programming languages (Santorini & Kroch 2000).
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05 • detailing each category of the predesign-phase
This chapter describes the formulation process as well as the design phase where it occurs – the pre-design phase. The main objective is to provide a better understanding of the formulation framework and, at the same time, to generate the sketch of its semantic ground, that is, a consensual vocabulary to enable appropriate specifications (or the “communication acts” towards design solutions. The main categories of information that compose the framework are: Strategic plans Codes and guidelines Contextual data Specifications for design.
context (problem)
PD1 data acquisition strategic plans (I) urban codes and guidelines (II) site and population context (III)
PD2 data translation pattern language 'specifications for design'
(IV)
design (solution)
1. 2. 3. 4.
27. The diagram shows the four different categories of the formulation process. Each one enclosing a crucial process within the pre-design framework (black text and boxes).
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The chapter 6 explores the most important formulation
category model:
of
the the
systemic language that is used by planners to formulate urban solutions, in short, the plannerâ&#x20AC;&#x2122;s language.
Chapter 6 6. The Sketch of a Planning Language
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6.1. Introduction Language, like a seed, is the genetic system which gives our millions of small acts the power from the whole (Alexander et al. 1977). The chapter 6 explores the most important category of the formulation model: the systemic language that is used by planners to formulate urban solutions, in short, the plannerâ&#x20AC;&#x2122;s language. When a designer is designing something, whether it is a house or a computer program or a stapler, s/he must make many decisions about how to solve problems. A single problem, documented with its most common and recognized good solution seen in the wild, is a single design pattern. Each pattern has a name, a descriptive entry, and some crossreferences, much like a dictionary entry. A documented pattern must also explain why that solution may be considered a good one for that problem, in the given context. How to describe such a language? The description of a specific domain language beyond natural languages requires an appropriate disclosure of its specific system. The first step to find out how language is structured is by searching deep its semantic field, here consisting of particular meanings encoded in the form of patterns. Another complementary way is to explore the structure of language in the way subjects are described (in multiple combinations), to understand how logic is created. To better understand this process is important to discover the way natural languages function.
6.2. The nature of language Language is a system of signs to express meanings - a simple algorithm to produce communication. What seems to be interesting in the universe of communication is the analogy that can be established between different fields of knowledge that seem to be linked by equivalent concepts. This seems to be the case of the planning language and the linguistics theory. Natural language is composed of a sort of definitions supported by:
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a) a syntax and b) semantics.75 While syntax corresponds to structure, semantics is associated with meaning (Chomsky 1965). Together they compose a medium for communication - a definition that seems to fit in the description of the planning language. Such a link was established in the â&#x20AC;&#x2DC;70s by Christopher Alexander (1977) who inspired by natural languages attempted to adapt the linguistics76 concept to planning.
6.3. Semantics and Syntax
Now, a closer look at the main components of language. In summary, language is composed by: a) syntax, which contains Classes - taxonomies of â&#x20AC;&#x153;speechâ&#x20AC;? (ideas / semantic level), Inflections - changes or mutations of the language ingredients, and Codes - description of possible combinations, and b) semantics, which is based on cognitive schemas that are mental models of different aspects of the world, containing knowledge, opinions, suppositions, associations, and expectations.
75 . Semantics is the study of meaning, usually in language. The word "semantics" itself denotes a range of ideas, from the popular to the highly technical. It is often used in ordinary language to denote a problem of understanding that comes down to word selection or connotation. This problem of understanding has been the subject of many formal inquiries, over a long period of time. In linguistics, it is the study of interpretation of signs or symbols as used by agents or communities within particular circumstances and contexts. Within this view, sounds, facial expressions, body language, and proxemics have semantic (meaningful) content, and each has several branches of study. In written language, such things as paragraph structure and punctuation have semantic content; in other forms of language, there is other semantic content. The formal study of semantics intersects with many other fields of inquiry, including proxemics, lexicology, syntax, pragmatics, etymology and others, although semantics is a well-defined field in its own right, often with synthetic properties. In philosophy of language, semantics and reference are related fields. Further related fields include philology, communication, and semiotics. The formal study of semantics is therefore complex. Semantics is sometimes contrasted with syntax, the study of the symbols of a language (without reference to their meaning), and pragmatics, the study of the relationships between the symbols of a language, their meaning, and the users of the language (Yule 2006). 76 . Linguistics is the scientific study of natural language. Linguistics encompasses a number of sub-fields. An important topical division is between the study of language structure (grammar) and the study of meaning (semantics and pragmatics). Grammar encompasses morphology (the formation and composition of words), syntax (the rules that determine how words combine into phrases and sentences) and phonology (the study of sound systems and abstract sound units). Phonetics is a related branch of linguistics concerned with the actual properties of speech sounds (phones), non-speech sounds, and how they are produced and perceived. Other sub-disciplines of linguistics include the following: evolutionary linguistics, which considers the origins of language; historical linguistics, which explores language change; sociolinguistics, which looks at the relation between linguistic variation and social structures; psycholinguistics, which explores the representation and functioning of language in the mind; neurolinguistics, which looks at the representation of language in the brain; language acquisition, which considers how children acquire their first language and how children and adults acquire and learn their second and subsequent languages; and discourse analysis, which is concerned with the structure of texts and conversations, and pragmatics with how meaning is transmitted ba sed on a combination of linguistic competence, non-linguistic knowledge, and the context of the speech act.
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The language is also structure by a sort of combinations, namely by: b1) structuring sounds into digitized segments (phonemes) which are sequenced into fixed combinations (words/morphemes); b2) treating these sequences as symbols for concepts (meanings) that can be used in many different situations; and b3) organizing sequences of words/morphemes into hierarchical phrases and sentences (syntactic structures) whose meanings are constructed systematically from the meanings of the words (Chomsky 2002).
Alexander’s pattern language (PL) (1977) is organized in a similar way despite its specific vocabulary involving space and people, public and private, natural and artificial things and concepts. As natural languages, PL morpho-syntax describes the elements of language. For example, PL number 19 relates to shops, people needs, centres, services, and then organizes them into a simple sequence of meanings (three interdependent concepts); “catch basis” 77 for services to serve people’s needs. At the end, it sets a design solution; the creation of a “web of shopping”. In what consists PL structure? Alexander considers that planning language has a more complex functioning than a tree of hierarchies as proposed by Chomsky for natural languages (Chomsky 1965). For Alexander such a tree does not explain language usage, since language seems to depend much more on the type of selection of the lexicon to produce particular results that express particular meanings. Alexander calls it semi-reticulated language due to its recursive and combinatorial system based on user multiple choices and heuristics. Diagram 28 represents a Chomsky’s tree structure 78 hierarchy for natural languages, dissimilar from Alexander’s PL.
77. Alexander’s expression. 78 . A tree structure is a way of representing the hierarchical nature of a structure in a graphical form. It is named a "tree structure" because the classic representation resembles a tree, even though the chart is generally upside down compared to an actual tree, with the "root" at the top and the "leaves" at the bottom. In graph theory, a tree is a connected acyclic graph (or sometimes, a connected directed acyclic graph in which every vertex has indegree 0 or 1). An acyclic graph which is not necessarily connected is sometimes called a forest (because it consists of trees).
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28. Language processing79
What are the main concepts of modern linguistics that fit in the planner´s language? In linguistics theory language is described as a semantic phenomenon “situated in the mind of the user” based on cognitive schemas (CS) (Croft & Cruse 2004) that represent mental models of different aspects of the world. In design languages such a cognitive process could be interpreted as the creative facet of planners. CS are difficult to encode into the formulation model once it represents an important aspect of the planner’s role within the design process. It is possible to establish analogies between modern linguistics theories and design languages, which supports the idea that planners possess an analogous system of communication. A closer look at three important concepts of modern linguistics is revealing and useful for the remaining of our discussion: 1) Mentalism - Where language is situated in the minds of speakers. Herein language is an idealization of the practices of a homogeneous community with a vast individual variation and mixture - where every speaker commands a number of different records of vocabulary and usage to be used in different contexts (Katz 1964). 2) Combinatoriality - Where language is a combinatorial system that can be used creatively and systematically following a non conscious process. Linguistics and psycholinguistics are concerned with discovering such a process as recent research on psychology of vision suggests. Herein the important question concerns what aspects of language does a speaker store in memory (including words, but also much else), and what does a speaker construct in the course of speaking? The latter involves the use of rules/schemas/principles that are applied creatively (Sugita & Tani 2005).
79 . Language processing refers to the way human beings process speech or writing and understand it as language. Most recent theories back the idea that this process is made completely by and inside the brain.
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3) Inner resources for language learning - Where one acquires language by learning on the basis of experiencing practices community. Herein the important question is what are the inner resources that one brings to such a task? Some of the resources are fairly general (e.g. ability to interact socially, ability to imitate). But some are specific to language, a “language instinct” - a cognitive specialization of humans (Manning & Schütze 2002).
6.4. Planners and Language processing Planners manage creativity by formulating associations or bridges between patterns in a process of multiple combinations – similar to the concepts of modern linguistics described above. Such a process is related with two different aspects of creation: systematization and instinctiveness. Formagio (1976) citing Heidegger refers that a piece-of-art is an exercise of design over meaning only present within a context of illumination (systematization) and occultation (instinctiveness). Creativity seems thus to enclose; 1) revealed information (systematized) and 2) unexpected information (created by associations and inner management).
Several studies focused on design phenomenology have targeted their case-studies at the iterative nature of creation. The aim of such protocol80 studies is the disclosure of the action paths that occur during a planning phase when resolution and judgment (decision making) are focal points. One of the techniques used is centred on monitoring discussions, drawings, and comments of design teams, capturing the flow of ideas that lead to decisions and design outputs.
80 . In natural sciences a protocol is a predefined written procedural method in the design and implementation of experiments. Protocols are written whenever it is desirable to standardize a laboratory method to ensure successful replication of results by others in the same laboratory or by other laboratories. Detailed protocols also facilitate the assessment of results throug h peer review. Protocols are employed in a wide range of experimental fields, from social science to quantum mechanics. Written protocols are also employed in manufacturing to ensure consistent quality. Protocol is also an agreement that governs the procedures used to exchange information between cooperating entities; usually includes how much information is to be sent, how often it is sent, how to recover from transmission errors, and who is to receive the information.
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In a similar study, Lindekens (2004; 2007) describes a monitored process showing a sample of solutions generated by a planning team. Moreover he describes how solutions are converted into designs and how designs express personal assumptions in a cycle that flows continuously. Such framework is useful to understand how humans behave when manipulating concepts in order to produce results. The recognition and the description of these heuristics 81 represents an opportunity for the definition of a common set of procedures with the objective of creating design solutions in a more organized and systematic fashion.
5.
Active drawing phase during the design (Lindekens 2004)
The following lines were taken from the discussion between planning team members. This “chat” and drawing session was recorded by Lindekens (2004) as part of his research. Herein team members express verbally their thoughts while making a set of sketches depicted in the above figure. The session was recorded and surveyed for a time period (follows an extract of the team’s comments). 0:43:54 - actually an important circulation … connection is still between… 0:44:03 - the elbow of the mill here 0:44:05 - because here the important steps are situated 0:44:08 - also the shortcut towards auditorium “de molen” [the mill] 0:44:12 - so this is an important circulation 0:44:17 - we the stairs over here … 0:44:20 - will be restored
81 . Heuristic is an adjective for experience-based techniques that help in problem solving, learning and discovery. A heuristic method is particularly used to rapidly come to a solution that is hoped to be close to the best possible answer, or 'optimal solution'. Heuristics are "rules of thumb", educated guesses, intuitive judgments or simply common sense. A heuristic is a general way of solving a problem. In more precise terms, heuristics stand for strategies using readily accessible, though loosely applicable, information to control problem solving in human beings and machines (Dechter & Pearl 1987).
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0:44:21 - the former stairs are continued till the ground floor 0:44:25 - so that a better connection is created that … 0:44:30 - that corridor with the gothic arches … towards … the stone staircase 0:44:37 - so we will make sure that this actually is the most important 0:44:41 - the most important route 0:44:43 - maybe here somewhere...
This fragment is insufficient to evaluate the planner’s language. The mechanism of thoughts is difficult to understand, although it often seems to follow a random order where concepts and scales are presented without a particular logical sequence. In such mechanisms, cognitive assumptions are usually abundant in problem solving82. In fact, one of the challenges in the elaboration of the formulation model is to create a system of predefined rules to avoid randomness, enabling at the same time the contribution of planner’s cognitive assumptions. The idea is to provide a logical structure to the model, as well as flexibility and manipulability.
6.5. Lexicon The elaboration of “speech” in a language requires the manipulation of a lexicon (or vocabulary). The urban design language enables a specific speech that entails a particular glossary associated with spatial features. The difficulty related with such lexicon is the vagueness of its semantic field and the breadth of its context. This is why it is so important to create an ontology to define a right path towards the description of the urban lexicon. How lexicon can thus be described? The urban lexicon consists of descriptions of single entities (vocabulary) that compose of groups of entities (patterns) ranging from concepts, geometric representations, land classifications, urban object’s descriptions, to physical delimitations (see Diagram 29), etc. Lexicon is thus the descriptive basis of patterns. The way lexicon is combined to define patterns is in the way different matters concerning urban space converge to form concepts (for space). Diagram 29 gives an idea about such type of convergence.
82 . Problem solving is a mental process and is part of the larger problem process that includes problem finding and problem shaping. Considered the most complex of all intellectual functions, problem solving has been defined as higher-order cognitive process that requires the modulation and control of more routine or fundamental skills. Problem solving occurs when an organi sm or an artificial intelligence system needs to move from a given state to a desired goal state (Goldstein & Levin 1987).
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In the diagram, the abstract pattern entity located at its centre connects to a variety of matters such as economy, geometry, population, boundaries, rules, etc. These matters correspond to the vocabulary that supplies patternâ&#x20AC;&#x2122;s semantics. Put simply, urban patterns are made of a combination of entities (lexicon) and Diagram 29 depicts the basic ontological structure of urban patterns.
29. The ontological diagram of an urban pattern (Montenegro, N.C. and Duarte, J.P., 2008)
Concluding with a simple syllogism: A given amount of entities or subject matters (a patternâ&#x20AC;&#x2122;s lexicon) congregated, create a pattern. The value and the combinations established between these subject matters enable the creation of a set of different patterns. A consistent set of patterns, running collectively, creates a particular language.
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6.6. Pattern Language The creation of a formulation instrument for urban design, proposed in this research, is inspired in the principles described in Alexander’s series of books published in the 70’s, which has created a new theory for urban design. “A pattern language”83 (PL) provides a method for designs based on a language of patterns for things ranging from rooms to towns. The “Timeless Way of Building” (Alexander 1979) provides the theory and instructions for the use of the language that made it possible to
use the patterns to create a building or a town. Alexander’s premises depart from linguistics theory, which defines language as a combinatorial and creative method of communication in different contexts, with clear instructions, and within a defined vocabulary. The aim for this language is to allow users to manipulate creatively its ingredients to develop an appropriate speech that is a design adequate to a given context. In planning, such characteristics are particularly useful for enabling a creative and flexible process. Pattern Language main concepts Pattern Language is a term denoting elements of language (Alexander et al. 1977). In the formulation model presented here, language is the metaphor for urban design whilst urban space. Patterns or elements of language correspond then to recurrent urban features or events where each pattern has a particular structure described by; a) a composition with a set of minor elements related to urban space, b) a definition of a recurrent urban problem or event, and c) a description of a solution to solve the urban problem. Patterns are akin to recipes in which by combining a collection of ingredients or metadata 84 according to specified routines one may arrive at adequate descriptions of solutions and then at solutions themselves through design generation.
83 . Patterns hide a lot of cultural and conceptual "baggage," providing a compressed intensity and an economy of expression in return. Patterns users who experience the power of patterns have acquired this baggage, either tacitly (through repeated use) or explicitly, by studying the literature. This is the opposite of models, for which syntax and semantics act as decoder rings for the model message. But it also explains the complementary ability of models and patterns as tools for successful and quality-focused software development (Evitts 2000). 84 . The first use of the term “Metadata” has been attributed to Jack E. Myers who subsequently trademarked the word. Since then the fields of library science, information technology and GIS have widely adopted the term. In these fields the word metadata
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The idea of recurrence85 within patterns was developed by Alexander and defines an important logic within the language and its syntax, that is the combinatorial and recursive way patterns can be manipulated allows one to use them indefinitely and extensively. This feature permits one to use the language in a creative way. Urban patterns are basically formulated to assist planners 86. Thus planners are pattern administrators possessing an intermediary level of intervention towards the development of solutions. In the formulation model patterns should generate some kind of proficient solutions even with a low managing intervention of planners. This means that the formulation model comprise a mechanism for, departing from a description of a context; arrive at a description of a solution.
Formulation patterns, which are deeply inspired in Alexander’s formalities, follow its basic scheme, that is; 1) all patterns have the same format, 2) patterns are defined by a picture with the archetypal example of the pattern, 3) each pattern has an introductory chapter that sets its context, 4) patterns are defined by one or two sentences defining the essence of its problem, 5) the problem is described in the longest section of the structure – pattern background, its validity, and the ranges of its manifestation, 6) the solution, the heart of the pattern, given by a set of precise instructions to guarantee instances of patterns, 7) the description of the solution in a diagram with its main components,
is defined as “data about data”. While this is the generally accepted definition, various disciplines have adopted their own more specific explanation and uses of the term (Dudley n.d.). 85 . In mathematics, a recurrence relation is an equation that recursively defines a sequence: each term of the sequence is defined as a function of the preceding terms. 86 . • From a broad perspective, a pattern can be seen as a form for documenting best practices. In a profession that lacks centuries of experience and scientific underpinnings of engineering, architecture, or urban planning, best practices have become a touchstone for ensuring that risks are understood and that commonly accepted techniques and technologies are used. Patterns provide a standard format and repository for them—replacing what has been, until now, anecdotal reporting and documentation of the best ways to do things. • From a narrower perspective, a pattern can be seen as a rule of thumb: a heuristic—quick way of providing a starting point for solving a problem. The craft of software development has generated many rules of thumb in its brief history. Patterns can provide a home for them that is formalized without being fussy. • Finally, and even more narrowly, a pattern can be viewed and used as a template. This definition captures a critical aspect of patterns: they can be applied over and ov er again, in different situations. They are not specific solutions, but rather the basis for a solution. And, in software development, they derive from the fact that software solutions themselves tend to be repetitive. There is only a small set of solutions for any design problem in information systems, whether the problem is in software architecture or in development organization (Evitts 2000).
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8) the set of smaller patterns related with the specific pattern in order to complement or enrich its description (similar to (Alexander’s, 1977: xi)).
The following text corresponds to a stretch from the Alexander’s Pattern Language book (1977). Texts and figures are taken from the book to portrait the above pattern structure. The pattern shown in following is the 26th of Alexander’s patterns, called “Life Cycle”.
”26. LIFE CYCLE (…) real community provides, in full, for the balance of human experience and human life - COMMUNITY OF 7000 (12). To a lesser extent, a good neighborhood will do the same IDENTIFIABLE NEIGHBORHOOD (14). To fulfill this promise, communities and neighborhoods must have the range of things which life can need, so that a person can experience the full breadth and depth of life in his community (…) Therefore Make certain that the full cycle of life is represented and balanced in each community. Set the ideal of a balanced life cycle as a principal guide for the evolution of communities. This means: 1. That each community include a balance of people at every stage of the life cycle, from infants to the very old; and include the full slate of settings needed for all these stages of life; 2. That the community contain the full slate of settings which best mark the ritual crossing of life from one stage to the next.
To live life to the fullest, in each of the seven ages, each age must be clearly marked, by the community, as a distinct well marked time. And the ages will only seem clearly marked if the ceremonies which mark the passage from one age to the next are firmly marked by celebrations and distinctions. By contrast, in a flat suburban culture the seven ages are not at all clearly marked; they are not celebrated; the passages from one age to the next have almost been forgotten. Under these conditions, people distort themselves. They can neither fulfill themselves in any one age nor pass successfully on to the next. Like the sixty-year-old woman wearing bright red lipstick on her wrinkles, they cling ferociously to what they never fully had. This proposition hinges on two arguments. a) The cycle of life is a definite
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psychological reality. It consists of discrete stages, each one fraught with its own difficulties, each one with its own special advantages. b) Growth from one stage to another is not inevitable, and, in fact, it will not happen unless the community contains a balanced life cycle. (â&#x20AC;Ś) To re-create a community of balanced life cycles requires, first of all, that the idea take its place as a principal guide in the development of communities. Each building project, whether the addition to a house, a new road, a clinic, can be viewed as either helping or hindering the right balance for local communities. We suspect that the community repair maps, discussed in The Oregon Experiment, Chapter V (Volume 3 in this series), can play an especially useful role in helping to encourage the growth of a balanced life cycle. But this pattern can be no more than an indication of work that needs to be done. Each community must find ways of taking stock of its own relative "balance" in this respect, and then define a growth process which will move it in the right direction. This is a tremendously interesting and vital problem; it needs a great deal of development, experiment, and theory.
STAGE x
IMPORTANT SETTINGS
RITES OF PASSAGE
INFANT 1
Home, crib, nursery, garden
Birth place, setting up the home . . . . out of the crib, making a place
trust YOUNG 2
Own place, couple's realm, children's realm,
CHILD
commons, connected play
Walking, making a place, special birthday
autonomy CHILD 3
Play space, own place, common land,
First ventures in town . . . joining
Initiative
neighborhood, animals
YOUNGSTER 4
Children's home, school, own place, adventure
Puberty rites, private entrance paying your
Industry
play, club, community
way
YOUTH 5
Cottage, teenage society, hostels, apprentice,
Commencement, marriage, work, building
Identity
town and region
YOUNG 6
Household, couple's realm, small work group,
Birth of a child, creating social wealth . .
ADULT
the family, network of learning
building
ADULT 7
Work community, the family, town hall, a room
Special birthday, gathering, change in work
Generativity
of one's own
OLD 8
Settled work, cottage, the family, independent
PERSON
regions
Intimacy
Death, funeral, grave sites
Integrity
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The rites of passage are provided for, most concretely, by HOLY GROUND (66). Other specific patterns which especially support the seven ages of man and the ceremonies of transition are HOUSEHUOLD MIX (35), OLD PEOPLE EVERYWHERE (40), WORK COMMUNITY (41), LOCAL TOWN HALL (44), CHILDREN IN THE CITY (57), BIRTH PLACES (65), GRAVE SITES (70), TEENAGE SOCIETY (84), CHILDREN'S HOME (86) (…)”
This pattern is an example of the PL language scheme, which consists of links established between the working pattern (26) with minor patterns (12), (14) of the language, as well as with major patterns as (66), (35), (40), (41), (44), (57), (65), (70), (84), (86). Pattern (66) denotes dominance over the others. The following diagram shows the 26th PL ontology taxonomy.
working pattern major patterns related
14
12
minor patterns related
26 66
35
40
41
44
57
65
70
84
86
30. An example of Pattern’s taxonomy (the created links between patterns)
Such description helps one to understand the role of each particular pattern within the planning language. PL fragilities The work of Alexander stirred the field but had little practical impact. With a set of comparative examples is possible to detect latent fragilities in the description of PL sorts. For example, there are patterns that repeat analogous solutions (example: patterns 57 and 68) due to the PL scale structure. There is also a lack of key patterns relevant for design such as urban grids or network morphologies. Without them is very difficult to structure a plan. Some other PL patterns are embedded in very particular cultural contexts which constrains the possibility of a wider general use. Finally a large amount of PL patterns are applicable at a larger scale (the city scale for example) than site planning scale, which is the focus of the current.
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How then to select patterns? To define a contemporary pattern language for the site planning scale, one may exclude Alexander’s patterns based on three criteria: similar solutions, cultural context, and scale. In general, patterns that can be excluded on scale refer to urban facilities that are normally considered at a city scale (cemetery, sports facilities, etc). In the elaboration of a plan at a site scale many of such patterns may have no applicability. However, if necessary, city scale patterns can be inherited by site scale patterns in order to match SUP/SD criteria (PDP1). Such patterns can then be included in the program. One possible way of managing large scale patterns is to create a module for them, in order to prevent the creation of a pattern language with a high number of exceptional patterns. To exclude patterns based on cultural criteria is more difficult, in a simplified model, due to the complexity and the extension that involves such descriptions. To surpass this difficulty one proposes a formulation “module”. The idea is simple. The basic structure of the formulation model is built on an agreed set of structural patterns, where modules can be added or removed to adjust the language of the program to the context of the plan and to the users of the urban program. The modules will include, among others, different cultural contexts and theoretical models of the city. This means that, this way, the formulation model is built in an extensible and combinatorial way, and it will be always a work in progress. This flexibility sets one of the key concepts of the proposed model. The assessment of related studies in order to revise and improve PL concepts and patterns might be necessary in the development of a contemporary pattern language. Thus a set of new patterns has to be introduced into the language to take into account new knowledge, models, and theories. PL patterns might also have to be improved regarding aspects such as data attributes, indicators and cross-references. In summary: 1. It is necessary to bring-up-to-date and redefine Alexander’s “pattern language”, having into account: 1.1 the advances in knowledge that occurred since the initial definition of the “pattern language,” and 1.2 the evolution of the cultural context (communities do not live today as before). 2. This redefinition can imply:
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2.1 the elimination of patterns, 2.2 the inclusion of new patterns, and 2.3 the modification of patterns.
The entire redefinition of the pattern language, and the addition of new final patterns will be the subject of future work, however, it is crucial to present a preliminary list of selected patterns. Urban patterns selected from Alexander’s PL patterns This section is concerned with a tentative list of urban patterns that apply at the site planning scale elaborated after Alexander’s list. In this a list, patterns that do not apply at the site planning are out of the list or are written in red. Patterns that are usually applied at a larger scale but occasionally also at the site planning scale are written green. Patterns that could be applied at the site planning scale but were excluded are written in blue. The list is the following: TOWNS SCALE
29. DENSITY RINGS
10. MAGIC OF THE CITY
30. ACTIVITY NODES
11. LOCAL TRANSPORT AREAS
31. PROMENADE
12. COMMUNITY OF 7000
32. SHOPPING STREET
13. SUBCULTURE BOUNDARY
33. NIGHT LIFE
14. IDENTIFIABLE NEIGHBORHOOD
34. INTERCHANGE
15. NEIGHBORHOOD BOUNDARY
35. HOUSEHOLD MIX
16. WEB OF PUBLIC TRANSPORTATION
36. DEGREES OF PUBLICNESS
17. RING ROADS
37. HOUSE CLUSTER
18. NETWORK OF LEARNING
38. ROW HOUSES
19. WEB OF SHOPPING
39. HOUSING HILL
20. MINI-BUSES
40. OLD PEOPLE EVERYWHERE
21. FOUR-STORY LIMIT
41. WORK COMMUNITY
22. NINE PER CENT PARKING
42. INDUSTRIAL RIBBON
23. PARALLEL ROADS
43. UNIVERSITY AS A MARKETPLACE
24. SACRED SITES
44. LOCAL TOWN HALL
25. ACCESS TO WATER
45. NECKLACE OF COMMUNITY PROJECTS
26. LIFE CYCLE
46. MARKET OF MANY SHOPS
27. MEN AND WOMEN
47. HEALTH CENTER
28. ECCENTRIC NUCLEUS
48. HOUSING IN BETWEEN
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49. LOOPED LOCAL ROADS
79. YOUR OWN HOME
50. T JUNCTIONS
80. SELF-GOVERNING WORKSHOPS AND
51. GREEN STREETS
OFFICES
52. NETWORK OF PATHS AND CARS
81. SMALL SERVICES WITHOUT RED TAPE
53. MAIN GATEWAYS
82. OFFICE CONNECTIONS
54. ROAD CROSSING
83. MASTER AND APPRENTICES
55. RAISED WALK
84. TEENAGE SOCIETY
56. BIKE PATHS AND RACKS
85. SHOPFRONT SCHOOLS
57. CHILDREN IN THE CITY
86. CHILDREN'S HOME
58. CARNIVAL
87. INDIVIDUALLY OWNED SHOPS
59. QUIET BACKS
88. STREET CAFE
60. ACCESSIBLE GREEN
89. CORNER GROCERY
61. SMALL PUBLIC SQUARES
90. BEER HALL
62. HIGH PLACES
91. TRAVELER'S INN
63. DANCING IN THE STREET
92. BUS STOP
64. POOLS AND STREAMS
93. FOOD STANDS
65. BIRTH PLACES
94. SLEEPING IN PUBLIC
66. HOLY GROUND 67. COMMON LAND
BUILDINGS SCALE
68. CONNECTED PLAY
95. BUILDING COMPLEX
69. PUBLIC OUTDOOR ROOM
96. NUMBER OF STORIES
70. GRAVE SITES
97. SHIELDED PARKING
71. STILL WATER
98. CIRCULATION REALMS
72. LOCAL SPORTS
99. MAIN BUILDING
73. ADVENTURE PLAYGROUND
100. PEDESTRIAN STREET
74. ANIMALS
101. BUILDING THOROUGHFARE
75. THE FAMILY
102. FAMILY OF ENTRANCES
76. HOUSE FOR A SMALL FAMILY
103. SMALL PARKING LOTS
77. HOUSE FOR A COUPLE
104. SITE REPAIR
78. HOUSE FOR ONE PERSON
105. SOUTH FACING OUTDOORS
Embedded concepts of patterns Patterns are different because its concepts and descriptions depend on the point of view of its developers. So to surpass this univocal picture it is important to look at related studies, first to become aware of different visions, and then to ease the selection of the formulation language structure.
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Alexander (1977) and Pedro (2001b) are good examples of such dissimilarity. They present two different visions regarding the development of patterns. Alexander has created a sort of language for design - the Pattern Language book87 is ample on semantics. The work of Pedro is largely framed by the universe of the quality standards - Pedro’s patterns deals essentially with quality attributes. While Alexander lacks main design actions as the creation of urban grids, focusing extensively on political ideals, Pedro seems to lack flexibility and narrative 88. Alexander supports its vision upon a liberal philosophy. When defining patterns such as “Dancing on the Streets” (PL 63) or “Sleeping on Public” (PL 94) it proposes ethics - often in opposition with traditional conventions regarding the use of space. PL embraces thus a creative vision by setting up desirable environments - however it seems too vague and too politically framed. Pedro supports its vision on a more prescriptive philosophy focusing quality demands for a site and a population. When defining a type of spatial quality he defines it following a constrained path to guarantee accuracy according to predefined parameters. A contemporary PL In the update of the pattern language it must be taken into consideration these two different visions concerning the formulation process. In the one hand, it is important to increase the accuracy of the language, as Pedro did, and on the other hand, it is necessary to maintain sufficient conceptual and visionary paths like Alexander. A balance between such different conceptions can bring benefits to the formulation model, because it amplifies the range of knowledge and manipulation.
87 . A Pattern Language: Towns, Buildings, Construction is a 1977 book on architecture. It was authored by Christopher Alexander , Sara Ishikawa and Murray Silverstein of the Center for Environmental Structure of the University of California at Berkeley, , with writing credits also to Max Jacobson, Ingrid Fiksdahl-King and Shlomo Angel. Twenty five years after its publication, it is still one of the best-selling books on architecture. The book is a substantive, illustrated discussion of a pattern language derived from traditional architecture, with 253 unitary patterns such as Main Gateways given a treatment over several pages. It is written as a set of rules that are invoked by circumstances. This is a form that a theoretical mathematician or computer scientist might call a generative grammar. The work originated from an observation that many medieval cities are attractive and harmonious. The authors said that this occurs because they were built to conform with local regulations that required specific features, but freed the architect to adapt them to particular situations. The book provides rules and pictures, and leaves decisions to be taken from the precise environment of the project. It describes exact methods for constructing practical, safe, and attractive designs at every scale, from entire regions, through cities, neighborhoods, gardens, buildings, rooms, built-in furniture, and fixtures down to the level of doorknobs. 88 . A narrative is a story that is created in a constructive format (as a work of writing, speech, poetry, prose, pictures, song, motion pictures, video games, theatre or dance) that describes a sequence of fictional or non-fictional events. It derives from the Latin verb narrare, which means "to recount" and is related to the adjective gnarus, meaning "knowing" or "skilled". (Ultimately derived from the Proto-Indo-European root gnō-, "to know"). The word "story" may be used as a synonym of "narrative", but can also be used to refer to the sequence of events described in a narrative. A narrative can also be told by a character within a larger narrative. An important part of narration is the narrative mode, the set of methods used to communicate the narrative through a process called narration.
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6.7. Urban Pattern Language Sketch (UPL) Until now, the research was essentially focused on a variety of topics related with language processing and planning methods. Now, it is time to build up the base (or the structure) of the planner´s language. Facing the considerable variety of matters involving the description of such a structure a question arises: Where to start? First of all, it is important to mention that pre-design ontology (the core process of this research) requires the sketch of an urban pattern language (UPL) to be used as a contemporary flexible tool by planners. The axiom UPL is not an obsessive premise. It basically drafts the name to distinguish it from other studies. So, herein, urban pattern language will be written UPL in order to differentiate from Alexander’s PL (pattern language). Some overlapping with PL is expected, though the word urban was chosen due to the exclusive field of application, the word pattern because it concerns type and value within the urban formulation, language due to the similarity with natural language’s structure. How does UPL work in the proposed model? The flow of information of UPL patterns acts at two different levels: one within the formulation model and the other in association with the generation (design) and evaluation models. The first level is simple to describe. Acquired data (PD1) acts as an input of the formulation model. Such data is interpreted in order to be embedded into patterns to support and guide design decisions. The second level consists of a data recursion process where data is in updating flow (between formulation, generation and evaluation models) to compose more integrated results. Evaluation is particularly important in such a process because it can act between patterns and design correcting and updating the entire flow.
6.8. The UPL Ontology The creation of a language’s ontology faces a set of difficulties. When one starts to handwrite a diagram following the principles of “classic” ontology-building is faced with a set of temptations (Gruber & others 1995). These concern mainly ambiguities prompted by the
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building a pre-design ontology: towards a model for urban programs
manual manipulation of elements, groups, classes, and types, within its taxonomic description. Such ambiguities drift from personal assumptions promoting a sense of vagueness in the partitions of the model. There is a critical problem between hand sketching and computational edition of ontologies. The computational edition of ontologies allows the emergence of relational structures, many of them without even having been previously imagined (Noy et al. 2000). Basically, the software asks a set of questions to the agent (heuristically) asking for new descriptions (domain, classes, and semantic attributes) (Sachs et al. 2006). Then the ontologybuilding is led by a sequence of emerging semantic relations, fill-in the empty spaces of the model. The mission of congregating all semantic relational data into the ontology is massive. One can initiate the process of organizing ingredients by a) describing a hierarchic tree of elements that compose of urban space (a taxonomy), then by b) describing a list of semantics that qualifies the urban elements (such as social, economic, and environmental features among others), and finally c) describing a list of attributes for the specified elements.
6.9. The UPL Syntax and Core Components
Developing an ontology is usually an iterative process. As aforementioned, one can start with a rough take at the ontology, and then revise and refine the evolving ontology by filling in the details. As mentioned in the methodology chapter, developing an ontology includes the following tasks: 1) definition of classes, 2) organization of the classes in a subclass-superclass hierarchy, 3) definition of slots by describing allowed values for such slots, and 4) the fill in the values for instances slots. Furthermore an ontology allows one to act on two complementary levels of description: a top level ontology on which are located the concepts and the relations of the model at a macro scale; and an application ontology which specifies and details the concepts, thereby describing the nature of its particular interactions.
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The initial task concerns the description of the core features of the UPL top level ontology. Such a selection requires a discovery of the crucial components of the urban planning process, that is: 1) The nature of urban space (the field of its application), 2) The nature of design actions (the field of its proposals), and the interoperability of these within, 3) A supporting computational system (the field of its administration).
These components are detailed as follows: 1) The nature of the urban space Kevin Lynch (1960) wrote that users understood their surroundings in consistent and predictable ways, by forming mental maps with defined elements: paths, streets, sidewalks, trails, and other channels in which people travel (Networks); edges, perceived boundaries such as walls, buildings (Blocks), and shorelines; districts, relatively large sections of the city distinguished by some identity or character (Zones); nodes, focal points, intersections or loci; and landmarks, readily identifiable objects which serve as reference points (Landmarks). Such classes are hence defined by a) Networks, b) Zones, c) Blocks, and d) Landmarks. 2) The nature of the design actions The urban design guidelines books surveyed for the current study recurrently presented similar descriptions (as in the ByDesign CABE, the Urban Design Compendium, or in the Green Dimensions books) (Gann et al. 2003)(Evans et al. 2007) (C. Moughtin & Shirley 2005). The core element that occasionally appears separated from the Lynchian outline is the Landscape element, somewhat denoting a tendency of planners to lead their actions based on this additional feature. The elements can be thus described as a) Networks, b) Zones, c) Blocks, d) Landmarks, and e) Landscape. 3) The supporting computational system A GIS (Geographic Information Systems) software platform will support the operability of the full model due to its resourceful spatial descriptors. Its representation standards encompass a) Points, b) Lines, and c) Polygons. The correlations seems to be clear: Landmarks can be represented by Points, Networks by Lines, and Blocks and Zones by Polygons. In summary, Lynchâ&#x20AC;&#x2122;s appraisal matches GIS core
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description while the element Landscape (a design action component) seems to promote fuzziness with the element Zones. Therefore the Top Classes will be herein defined as: a) Networks (Lines), b) Zones (Polygons I), c) Blocks (Polygons II), and d) Focal points or Landmarks (Points). However such a fuzziness limits the process understanding. To produce the ontology is thus necessary to congregate three concepts: 1) the nature of urban space, 2) the nature of design actions, and 3) the interoperability of these with a supporting computational system. The descriptions of patterns that will inform designs will follow the scheme: a) Networks (Lines), b) Zones (Polygons I), c) Blocks (Polygons II), and d) Focal points (Points). Now, describing the top ontological classes: Networks Networks appear here without having a hierarchical dominion over the other three core components of the program (blocks, zones, and focal points or landmarks). It just sets one of the possible four actions that planners can input into designs in a crucial phase of their work. The Network component can be described by a framework of routes and spaces that connect locally and more widely, and open spaces that are sequentially related to one another (Gann et al. 2003). This component upholds a strong social impact once streets make a large part of
peopleâ&#x20AC;&#x2122;s experience of place. They are the main spaces where people interact, and they combine their function as a place with a role as part of a movement network for vehicles and pedestrians (Evans et al. 2007). There are various classes of Networks depending on form and function. Networks involve mainly movement paths and infrastructure paths (Gann et al. 2003). Other type of more abstract networks can be related with landscape networks or building masses networks. Networks are divided into different class groups across different taxonomies. According to Lynch (1960) there are three main metaphors which attempt to explain city form through networks: the magical metaphor for the earliest ceremonial centres of religious ritual to link the city to the cosmos and to the environment; the metaphor that makes an analogy with a machine; and the metaphor that compares city form to an organism.
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According to Moughtin and Shirley (2005) these three metaphors are related to five main forms of urban grids: 1) hierarchy of boxes, each nesting another, 2) orthogonal geometrical figure / grid-iron plan, 3) directional grid, 4) triangular grid, and 5) informal lacework of paths. Marshall (2005) further describes the network system and details network movement patterns by describing performance correlation between different morphologies. Blocks Blocks represent compositions of buildings or groups of buildings within an urban site. The space in between the volumes of blocks generally implies movement grids. The mixture between blocks and grids defines the main structure of urban settlements. This component of the urban program involves street blocks arrangements with its plots and buildings in settlements (buildings < plots < blocks) (Gann et al. 2003). Buildings can range from housing, office areas, recreation, leisure, and sports to crèches, education, health, and training to community workspaces. Buildings within blocks also provide a secure base for community organisations to establish a presence by developing partnerships between locals and other stakeholders. Blocks also configure the best local resources to generate income (Evans et al. 2007). There are few studies committed to the definition of block morphologies and its classes within city descriptors. The existing ones seem to be vague or too classic. Once again, Alexander’s “pattern language” (1977) lacks this core category of “city objects”. When Alexander refers to blocks he avoids a physical or geometric recognition or description of it, setting a group of social semantics upon a vague notion of neighbourhood. Post-modern research (Krier & Porphyrios 1984) correlates blocks with types of classic archetypal morphologies while building masses tend today to be more abstract or topologic, sometimes inspired in natural forms, or even developed under conceptual art or technology. The range of block designs is today quite wide and open. Mitchell (1993) talks about an absence of a theoretical critic able to explain the origin of shapes. However the starting point to define block in a somewhat formalized way can be found in Pedro (2001b), where blocks descriptions comprise a set of flexible archetypal forms that can be parameterized. Zones The component Zones comprise areas within perimeters defining types of environments within sites. Zones are here defined within boundaries containing groups of meanings involving matters such as the range of services and facilities, including commercial, educational, health, spiritual and civic services (Evans et al. 2007). Design under this component is similar to
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“planning through portraits” (Lynch 1960) where concepts as neighbourhood and mixture represent a design core. Zones also require caution in the design process to avoid any form of segregation. It is therefore essential to promote diversity in terms of: a) development forms; b) land use; c) density; d) tenure; and e) market segments. Zones are usually carved into development parcels around a road system with a clear urban design structure in place (DETR 2000). This approach frequently involves routing the main road around the site rather than across it and locating the traffic generating uses such as retail and employment areas close to entrance junctions and along the main road. “The road is used as a boundary to segregate uses. Such attempts to create a sense of place around a focal point often fail because the very uses that generate activity are on the edge of the site or beyond, in a nearby business park or out-of-town centre, and tend to be internalised in “big boxes”(Evans et al. 2007). Focal Points or Landmarks The development of a plan can start with the identification or definition of focal points and/or landmarks in space (pre-existing or new). These marks act as structural nodes from which planners can define networks and masses of the plan. The relevance of landmarks and focal points is simple to portray (Gann et al. 2003); “People find it easier to orient themselves and recognise where they are when new development safeguards important views between places or creates new ones, whilst respecting or adding new local landmarks. To ensure that a particular place is legible, assess the relationship between existing elements and, in consulting local people, determine how proposals contribute to a linked series of spaces and markers that make it easy to get from A to B and to C” (Evans et al. 2007). The following diagram (31) shows the main classes of the pre-design phase. The core ontology (Blocks, Focal Points, Networks, and Zones) is located in the purple boxes of the diagram entities. Its shared super-class is Design Core (light purple and dark green boxes).
Diagram 31 is also presented in Annex 5 at a different scale.
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31. Syntax class hierarchical tree (above left), exported piece of XML Schema (above centre), CPL diagram classes, subclass-superclass hierarchy, and slots (middle right), CPL diagram zoom - the design core Networks, Zones, Blocks, and Landmarks (at the bottom). note: the CPL was built in the ProtĂŠgĂŠ-Frames editor, in accordance with the Open Knowledge Base Connectivity protocol (OKBC).
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6.10. The UPL lexicon A considerable part of the information related with urban space comprises geographic data, that is, information that describes territorial features. Such information type is currently shared by some communities and managed by central governments or controlled by other administrative organizations. These specific databases are internationally known as geographic information systems (GIS). The main purpose of such systems is the assemblage of relevant geographic data to produce comprehensive descriptions of spatial configurations. One of the advantages of GIS is related with its system of coordinates known as geo-reference, which means that geographic information is related to a precise location on the planet, within a continent, a region, or a site, and can be correlated with other geo-referenced information. Due to strong investments by state and private corporations with interests on property and territorial management, GIS software constitutes a well developed platform today. GIS thus represents an important resource to be used in the formulation model to quickly retrieve and store geographic data in the process of developing urban proposals. A GIS database can be used to feed the formulation model with data about the context. It also can be used to store data about designs produced by the generation module. Compatibility amongst both contextual and design data requires the definition of a common ontology. Such ontology will allow an easy flow of information within the formulation model and between this and the other two models of the planning process - the generation model and the evaluation model. At present there is an absence of an urban planning ontology covering the core matters of the urban planning process. One way of surpassing the difficulty of defining a totally new ontology is to use partial existing ones adapted to the needs of the formulation model. This creates the possibility of using ontological descriptions within existing GIS databases as the Spatial Data Transfer Standard (SDTS)89 approved by the US Federal Information Processing Standard (FIPS)
89 . Purpose of SDTS -- The purpose of the SDTS is to promote and facilitate the transfer of digital spatial data between dissimilar computer systems, while preserving information meaning and minimizing the need for information external to the transfer. Implementation of SDTS is of significant interest to users and producers of digital spatial data because of the potential for increased access to and sharing of spatial data, the reduction of information loss in data exchange, the elimination of the duplication of data acquisition, and the increase in the quality and integrity of spatial data. SDTS is neutral, modular, gro wthoriented, extensible, and flexible--all characteristics of an "open systems" standard. (http://data.geocomm.com/sdts/) accessed January 2009.
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90
(Rugg 1995), or the OpenGIS City Geography Markup Language (Kolbe, Gröger et al. 2005).
Those GIS “standards” were built to support operations between different computational systems within a data transfer philosophy based on geographic and cartographic information as well as other relevant metadata. This relevance demands a closer look at both systems: The SDTS – GIS The SDTS has a concept model consisting of detailed specifications such as content, structure, and format. The spatial data model structure is based on three types of object description: a) The “Spatial entities model”, which describes real spatial entities such as buildings, roads, rivers, and so on, through rate attributes, b) the “Spatial objects model”, which describes spatial objects such as lines, polygons and dots, used to represent real entities in digital systems and, c) the “Spatial descriptions model”, which describes entities related to the real world, objects related to the digital world, as well as spatial descriptions and connections that exist between them. To guarantee data homogeneity and compatibility between data transfer, SDTS describes a formal list of entities. The actual list includes more than 200 entity types, 244 attributes and more than 1200 alternative terms. The standard definition of entities includes the following data structure: a) “Entity type”, a definition of a set of similar entities, b) “Entity instance”, an example of a specific formalization within a type; “Attribute Entity”, a feature that describes a type, c) “Attribute value”, a specific quality of an attribute, d) “Standard expression”, a stereotyped name for an entity or an attribute, and e) “Integrated expression”, a synonym used to refer to an entity or an attribute, defined by SDTS rules (Rugg 1995). The OpenGIS – CityGML The OpenGIS City Geography Markup Language (Kolbe, Gröger et al. 2005) has a similar functional structure, with entities and classes definition that can be applied to the current study model. One of the relevant aspects of GIS within geographic data gathering is the focus on the creation of spatial ontologies (GIS-O). GIS spatial ontologies comprise today one of the most advanced fields of ontology research and implementation. GIS software applications are
90 . . OpenGIS® Encoding Standard is for representation, storage, and exchange of virtual 3D city and landscape models. CityGML is implemented as an application schema of the Geography Markup Language version 3.1.1 (GML3). CityGML models both complex and georeferenced 3D vector data along with the semantics associated with the data. In contrast to other 3D vector formats, CityGML is based on a rich, general purpose information model in addition to geometry and appearance information. For specific domain areas, CityGML also provides an extension mechanism to enrich the data with identifiable features under preservation of semantic interoperability.
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also widely implemented facilitating the access to classified data managed by institutions ranging from governmental institutes to private corporations as mentioned above. However, one of the recurrent problems involving GIS databases is the data sharing knowledge. This difficulty occurs particularly in Europe where GIS is largely administrated according to an individual management philosophy. In the U.S., GIS databases have a large public shared character although this seems to lead to lower quality. In this region GIS databases are financed and promoted by governments. The UPL lexicon could correspond to ontological sub-classes mainly taken from the CityGML GIS standards, which consists in vast class definitions for the most important types of objects within 3D city models. Its basic definitions representing the spatial objects and their aggregations are defined by ISO 19109 and GML3 standards, and it comprises different types of interrelationships between Feature Classes like aggregations, generalizations and associations. An important outcome of such descriptions is a high degree of semantic interoperability between different applications along their UML mapping, defining feature types, attributes, and data types with a standardised meaning or interpretation. Towards an ontological integration of descriptions the data is encoded by UML - Unified Modeling Language within its static structure diagram. The structure is simple. The base class of all thematic classes is CityObject. “CityObject is a subclass of the GML class Feature, thus it inherits its metadata (e.g. information about the lineage, quality aspects, and accuracy). The subclasses of CityObject comprise the different thematic fields of a city model: the terrain, the coverage by land use objects, transportation, vegetation, water bodies and sites, in particular buildings” (Kolbe, Gröger et al. 2005). CityFurniture is another GML class, and is used to represent traffic lights, traffic signs, flower buckets, or similar objects. The features that are not covered explicitly by them are modelled by the class GenericCityObject. However CityGML schema still lacks some descriptions of subclasses like tunnel, bridge, excavation, wall or embankment. At present, these objects have to be represented by GenericObjects, or will be defined herein by new classes. There is a normative to apply to Feature attributes: unless it is stated otherwise each feature has attributes classes, function, and usage. The class attribute can occur only once, while the attributes usage and function can be repeated within the ontology. The class attribute describes the classification of objects, e.g. road, track, railway, or square. For the purpose of an object, like national highway or county road, it is used the attribute function,
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while the attribute usage may define if an object is e.g. navigable or usable for pedestrians. The most relevant Top level classes are: Land Use, Building Model, City Furniture, Transportation Object, Vegetation Object, and Water Bodies (Kolbe, Grรถger et al. 2005). The following diagram presents the top level class hierarchy of the lexicon.
32. UML diagram of the top level class hierarchy (CityGML)
The figure below shows some of the CityGML object listed codes, that will be used in the edition of the language ontology, and which composes part of the vocabulary used in the above UML diagrams.
6.
An example of a CityGML code list for city objects
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6.11. The UPL Semantics
UPL semantics are key attributes of the formulation model enclosing performance91. These attributes bring up recursive data to fill in slots such as meaning and substance within the ontology. Such data is therefore crucial to compose the ontology of an urban program. The field of its application is mainly focused on: a) Events upholding the human quotidian life (social/safety patterns), b) Features as energy and environment control (bioclimatic patterns), and c) Features with a value sight (technology and economy patterns).
Where is located this semantic field in the ontology? The Alexander’s patterns are part of this semantic field and represent the core instrument of the ontology-building. In fact, the patterns that are here portrayed represent an addition to the Alexander patterns. These are the patterns that will be conjugated at the final pattern language redesign. The final organization of all these components of the planning language will be concluded in future research.
Now, a closer look at the item a) events upholding the human quotidian life (social/safety patterns).
a) Social core. CPL semantics are guided by the social nature of a site as described by the following: 1. Character – which is a place with its own identity. The idea is to “promote character in townscape and landscape by responding to and reinforcing locally distinctive patterns of development, landscape and culture”,
91 . . A performance indicator or key performance indicator (KPI) is a measure of performance. Such measures are commonly used to help an organization define and evaluate how successful it is, typically in terms of making progress towards its long -term organizational goals. KPIs can be specified by answering the question, "What is really important to different stakeholders?". KPIs may be monitored using Business Intelligence techniques to assess the present state of the business and to assist in prescribing a course of action. The act of monitoring KPIs in real-time is known as business activity monitoring (BAM). KPIs are frequently used to "value" difficult to measure activities such as the benefits of leadership development, engagement, service, and satisfaction. KPIs are typically tied to an organization's strategy using concepts or techniques such as the Balanced Scorecard. The KPIs differ depending on the nature of the organization and the organization's strategy. They help to evaluate the progress of an organization towards its vision and long-term goals, especially toward difficult to quantify knowledge-based goals. A KPI is a key part of a measurable objective, which is made up of a direction, KPI, benchmark, target, and time frame.
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2. Continuity and enclosure – which is a place where private and public spaces are distinguished. Here the concept is to promote the continuity of street frontages and the enclosure of space by development which defines private and public areas, 3. Quality of the public realm – which is a place with attractive and successful outdoor areas. The idea is to promote public spaces and routes that are attractive, that are safe, and work efficiently for all in society, including disabled and elderly people, 4. Ease of movement – which is a place that is easy to get to and move through. The idea is to promote accessibility by making places that are easy to move through and connect with each other, putting people before traffic and incorporating land uses and transport, 5. Legibility – which is a place that is easy to understand. The concept is to promote legibility through development that provides recognisable routes, intersections and landmarks to help people find their way around, 6. Adaptability – which is a place that can change easily. The idea is to promote adaptability through development that can respond to changing social, technological and economic conditions, and g) diversity – which is a place with variety and choice” (Gann et al. 2003).
The social quality needs to be evaluated through requirements such as security, spatial and functional potential, personalization and economy; which are applicable within the space relations of a particular site (Pereira 1996). Those are held to reinforce links between populations within their surrounding environment. Moreover further studies deepen the notion of social space comprising new urban research outcomes. This seems to be the case of the “The City Joust” of Guterres (2004) that consists of an innovative social study regarding urban planning. In “The City Joust”, social metrics are enclosed in the “experience of the city”, in a phenomenon that gauges the universe of the urban space relations, its intrinsic empathies and the social behaviours. The study presents an extensive study on social space measuring consequences implicit on public and private areas (as well as hybrid). It describes the impacts on the quality of a population’s everyday life. The concepts are supported by different theories and indicators, namely from Maslow (1954), Jacobs (1961), Hall (1973), Newman (1972), Hillier & Hanson (1984), and Coleman (1990).
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Those social patterns were encoded into new patterns, and transform into indicators as shown in the table 7.
Some of the created patterns are described as follows: 1. Empathy Distance (ea), 2. Public Green (pg), 3. Total Area With Sense of Sociability (tass), 4. Private Areas With or Without Social Interaction (pawwsi), 5. Public Area With Everyday Existence (pgee), 6. Sidewalks With Social Interaction (ssi), 7. Private Areas, or with Diaphragms, with Social Monitoring (padm), 8. Pedestrian Areas (pa) and, 9. Private Areas without Social Interaction (pawsi).
codes
ea pgee
calculations p1 (%) ea (m2/hab) p3 (%) pgee (m2/hab)
tass
p4 (%) tass (m2/hab)
ssi
p7 (%) ssi (m2/hab)
pg
p8 (%) pg (m2/hab)
pawsi
p10 (%)
pawsi (m2/hab) 7.
site values
indicators
12,0%
0 > desirable
79,56
0 > desirable
0,0%
> 3,5%
0,00 18,0%
> 25%
119,62 13,0%
> 20%
86,03
> 10
1,1%
10%
7,11
5
0,0%
< 6%
0,00
<3
The above table presents some indicators of Guterres social patterns (2004).
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The provisory codes and names for this sample are described by: GP ea1
GP ssi6,
GP pg2,
GP padm7,
GP tass3,
GP pa8,
GP pawwsi4,
GP pawsi9.
GP pgee5,
b) Sustainability core (environmental domain). UPL is also informed by sustainability factors. The definition of patterns encompassing such factors follows a basic set of concepts. In summary they require urban space to be: a) active, inclusive, and safe – which means that urban settlements needs to be fair, tolerant and cohesive with a strong local culture and other shared community activities; b) well run – this is related with an effective and inclusive participation, representation, and also leadership; c) environmentally sensitive – because is important to provide places for people to live that are considerate of the environment; d) well designed and built – which concerns the quality of the built and the natural environment; e) well connected – with good transport services and communication linking people to jobs, schools, health and other services; f) thriving – with a flourishing and diverse local economy; g) well served – with public, private, community and voluntary services that are appropriate to people’s needs and accessible to all; and h) fair for everyone – because is crucial to include minorities in communities, now and in the future (Evans et al. 2007). Further research will give depth to concepts and indicators defining the corpus of sustainability patterns. Despite such a framework some examples of sustainable patterns are presented as follows.
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b1) Bioclimatic. These patterns consist of a group of instruments inspired in the â&#x20AC;&#x153;Bioclimatic Urbanismâ&#x20AC;? domain (Higueras 1997). These studies are mainly focus on climatic features and urban environmental conditions. The main outcome is a set of design guidelines for green and open areas, buildings, volume orientations, etc., supported on energy and environmental sustainability criteria. Olgyay (1963)charts both architecture and climate attributing different urban forms for buildings in the four main world regions, establishing for each region design strategies that serve as guidelines to architects as much as to city planners. In this context building forms are shaped by temperature, sun exposure and humidity.
8.
Form and proportions of buildings in different regions (Olgyay 1963)
The formal descriptions of the climatic patterns (Higueras, 1997) traduce a set of standards towards the definition of form, setting itself as an essential support to develop climate-based formal features. The following example of a cold region reveals the relevance of climate for the definition of design solutions. In fact, each description of a climatic recommendation seems to enclose a relevant pattern for design. As an example I describe below patterns for the Cold Region (Higueras, 1997).
General considerations 1. Selection of a location. For sun exposure, slopes S and SE are most favourable. Locations on a mid slope are beneficial to prevent excessive effect of winds and avoid cold air. 2. Urban structure. Planning management has to provide protection against winds. Sets of constructions of a larger scale can be grouped, although maintaining free space between them to take advantage of the solar effect. Houses tend to be united to decrease the exposed surface as much as possible and avoid heat loss. 3. Public Spaces. These should be protected from the wind,
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open, and have with periodic shaded areas. 4. Landscape.
Topography, generally rough,
influences the definition of the forms of streets and the use of the space, granting it an irregular character. 5. Vegetation. The most favourable vegetal protecting barriers are those constituted by perennial vegetation, oriented according to the NE direction, and located within a distance of twenty times the height of its hoist. Near the houses should stand deciduous trees. Is should be avoided to locate vegetation near houses because it can produce humidity.
The design of the house 1. House Type. In residential arrangements, houses of one or two levels must favour compactness. Terraced houses offer the advantage of loosing less heat. In larger apartment buildings the compact volume is the better choice. 2. General distribution. Heating saving is three times more important than the provision of comfort in summer. Extreme conditions in summer and in winter suggest the creation of two separated zones that play the double roles in building. The location of steps in the outside and the presence of ramps for cars must be avoided. 3. Distribution Plan. Design will be governed by the predominant conditions in cold months. The period of “stay inside the house” represents 70% of annual hours. Although the plan will have to satisfy both conditions through compactness, it is essential to include additional zones of activity or use in deeper spaces for summer comfort. 4. Form and volume. The constructions must be compact and display a minimum exposed outer surface. A proportion of 1:1,1 or 1:1,3, along the East-West axis will give the finest results. 5. Orientation. The most favourable solar orientation is located to 12° SE. The predominant wind pattern NW-SE can influence the location of isolated buildings. 6. Colour. Surfaces exposed to the sun must have average tonalities. Surfaces can be made of absorbent dark colours, assuring that they will always be in the shade during the summer.”
These guidelines will be patterns or design rules only if they will be applied to generate patterns, that is, recurrent solutions for designs. The deference for these guidelines will generate descriptive patterns of properties of urban objects. In summary, the set of cold region patterns can be used to reinforce UPL semantics by complementing Alexander’s patterns. The provisory codes and names for these patterns are:
HP cr1. Selection of the location,
HP cr4. Landscape,
HP cr2. Urban structure,
HP cr5. Vegetation,
HP cr3. Public Spaces,
HP cr10. House Type,
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HP cr20. General distribution,
HP cr50. Orientation, and
HP cr30. Distribution Plan,
HP cr60. Colour.
HP cr40. Form and volume,
All these patterns will be tentatively added to the previously selected Alexander’s patterns, following the mentioned criteria. The list of Alexander’s patterns complemented with the added patterns is, therefore, organized as follows; AP lta11. LOCAL TRANSPORT AREAS
AP hb48. HOUSING IN BETWEEN
AP cm12. COMMUNITY OF 7000
AP llr49. LOOPED LOCAL ROADS
AP in14. IDENTIFIABLE NEIGHBORHOOD
AP tj50. T JUNCTIONS
AP nb15. NEIGHBORHOOD BOUNDARY
AP gs51. GREEN STREETS
AP wpt16. WEB OF PUBLIC
AP npc52. NETWORK OF PATHS AND
TRANSPORTATION
CARS
AP rr17. RING ROADS
AP mg53. MAIN GATEWAYS
AP fls21. FOUR-STORY LIMIT
AP rc54. ROAD CROSSING
AP pr23. PARALLEL ROADS
AP bpr56. BIKE PATHS AND RACKS
AP ss24. SACRED SITES
AP cc57. CHILDREN IN THE CITY
AP aw25. ACCESS TO WATER
AP qb59. QUIET BACKS
AP lc26. LIFE CYCLE
AP ag60. ACCESSIBLE GREEN
AP en28. ECCENTRIC NUCLEUS
AP sps61. SMALL PUBLIC SQUARES
AP dr29. DENSITY RINGS
AP ps64. POOLS AND STREAMS
AP an30. ACTIVITY NODES
AP hg66. HOLY GROUND
AP p31. PROMENADE
AP por69. PUBLIC OUTDOOR ROOM
AP ss32. SHOPPING STREET
AP sw71. STILL WATER
AP nl33. NIGHT LIFE
AP ls72. LOCAL SPORTS
APhm35. HOUSEHOLD MIX
AP ap73. ADVENTURE PLAYGROUND
AP dp36. DEGREES OF PUBLICNESS
AP sgwo80. SELF-GOVERNING WORKSHOPS AND
AP hc37. HOUSE CLUSTER
OFFICES
AP rh38. ROW HOUSES
AP sswrt81. SMALL SERVICES WITHOUT RED
AP ope40. OLD PEOPLE EVERYWHERE
TAPE
AP wc41. WORK COMMUNITY
AP oc82. OFFICE CONNECTIONS
AP nc45. NECKLACE OF COMMUNITY
AP ts84. TEENAGE SOCIETY
PROJECTS
AP ch86. CHILDREN'S HOME
AP mms46. MARKET OF MANY SHOPS
AP iws87. INDIVIDUALLY OWNED SHOPS
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AP sc88. STREET CAFE
AP fe102. FAMILY OF ENTRANCES
AP bh90. BEER HALL
AP spl103. SMALL PARKING LOTS
AP ti91. TRAVELER'S INN
AP sr104. SITE REPAIR
AP bs92. BUS STOP
AP sfo105. SOUTH FACING OUTDOORS
AP fs93. FOOD STANDS AP bc95. BUILDING COMPLEX
And more occasionally by:
AP ns96. NUMBER OF STORIES
AP i34. INTERCHANGE
AP cr98. CIRCULATION REALMS
AP lth44. LOCAL TOWN HALL
AP mb99. MAIN BUILDING
AP hc47. HEALTH CENTER
AP ps100. PEDESTRIAN STREET
AP bp65. BIRTH PLACES
AP bs101. BUILDING THOROUGHFARE
AP gs70. GRAVE SITES
All patterns are described by its codes as shown in the following list. The code is defined by: two capital letters, the first identifying the pattern’s author and the second confirming it as pattern (P) (example: AP – Alexander pattern), then, two or three small letters representing the particular axiom of the pattern (example: Birth Places – bp), finally, the relative number of each pattern. The following list congregates all provisional patterns discussed in this document. AP lta11
AP ss32
AP mg53
AP oc82
AP fe102
AP cm12
AP nl33
AP rc54
AP ts84
AP spl103
AP in14
APhm35
AP bpr56
AP ch86
AP sr104
AP nb15
AP dp36
AP cc57
AP iws87
AP sfo105
AP wpt16
AP hc37
AP qb59
AP sc88
AP i34
AP rr17
AP rh38
AP ag60
AP bh90
AP lth44
AP fls21
AP ope40
AP sps61
AP ti91
AP hc47
AP pr23
AP wc41
AP ps64
AP bs92
AP bp65
AP ss24
AP nc45
AP hg66
AP fs93
AP gs70
AP aw25
AP mms46
AP por69
AP bc95
HP cr1
AP lc26
AP hb48
AP sw71
AP ns96
HP cr2
AP en28
AP llr49
AP ls72
AP cr98
HP cr3
AP dr29
AP tj50
AP ap73
AP mb99
HP cr4
AP an30
AP gs51
AP sgwo80
AP ps100
HP cr5
AP p31
AP npc52
AP sswrt81
AP bs101
HP cr10
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HP cr20
HP cr60
GP pawwsi4
GP pa8
HP cr30
GP ea1
GP pgee5
GP pawsi9
HP cr40
GP pg2
GP ssi6
HP cr50
GP tass3
GP padm7
6.12. Conclusion Following Christopher Alexanderâ&#x20AC;&#x2122;s conceptual pathway it is straightforward to elaborate a relatively balanced and functional selection of patterns in order to provide for an efficient and effective urban pattern language. However, problems emerge after such selection, more precisely, when the task is to relate the selected patterns with each other (from so different domains)92 to build-up the syntax of the language. Up to this point, the focus was on organizing patterns according to scale. Alexander classified defined patterns based on scale because in a way it corresponds to a model of rational planning. As a model it seems as clear as it can be. However, city planners might select thematic fields of interest when planning and designing urban space. In this context, organizing patterns by scale seems to restrict some of the ideological facets of traditional planning activity. One of the future missions of our research is, therefore, to find an alternative taxonomy that can first be based on thematic urban problems, and only then controlled by scale considerations.
92 . Economic, climatic, social, regulatory, cultural, etc.
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05 â&#x20AC;˘ planners have their own language to plan - one will call it urban pattern language (UPL) This chapter explores the most important category of the formulation model: the systemic language that is used by planners to formulate urban solutions, in short, the plannerâ&#x20AC;&#x2122;s language.
PD2 data translation pattern language 'specifications for design' (IV)
In Diagram 33 is depicted the design core of the language.
33. The diagram shows the core structure of the CPL, first described in a hierarchical tree (above left), then in an exported piece of XML Schema (above centre), and finally in a diagram (ontology core - Networks, Zones, Blocks, and Landmarks (at the bottom)). See annex 5.
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Chapter 7 7. Conclusion
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7.1. The Context This thesis is part of a larger research which is concerned with the development and implementation of a computer model for urban design. The ultimate goal of this model is the development of a computer tool to assist in the conception and implementation of urban design plans at the site planning scale. This larger model includes three partial models and tools for formulating, generating, and evaluating such plans. This thesis is concerned with the formulation model, which aims at creating the programs of urban interventions from contextual data, including, regulations, site, and population data. It represents one step towards the development of this model and the corresponding tool. The thesis sketches an ontology and a pattern language for describing urban space and composing urban programs. The tool will consist of an interactive computer system that codifies a pattern language that can be used for describing urban solutions for predefined contexts, according to the ontology. The computer implementation of the ontology is the immediate following step in the research. Other future steps will be the inference of the rules that link particular contextual features to specific patterns and the computer implementation of the urban pattern language (UPL) defined in this way.
7.2. The Problem One of the main concerns related with the development of the formulation model and tool is the selection and definition of its core components and the efficiency of the embodied methodology. This first problem was solved to a certain extent in this thesis. A knowledge model in any domain requires an initial listing of the base concepts of that domain. The proposed ontology allowed one to indentify the main classes of such concepts, in order to structure the taxonomy of urban space that is manipulated in the planning activity. These classes are networks, blocks, zones, focal points, and landscape and they were compiled based on several previous studies. The ontology allows one to map the relationships among the entities and components of the model and to understand how they work. The methodology embodied in the formulation model concerns the series of steps that are necessary to follow in a certain order to arrive at the urban program departing from the
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context. So far, research permitted to link such a methodology to a large data model formed by key concepts, called patterns, and to the relations among them. Still, the relation between ontological objects and urban patterns is not completely clear yet. Are they the same type of entities? This is an important aspect to clarify in further research. It is our hope that in fact, the exhausting description of these concepts will allow one to understand the overall process as a vast relational database constituted of independent but interrelated parts (patterns and sub-patterns). So, future research will be concerned with using an ontology editor to describe the concepts and the relations among them exhaustively so as to arrive at the rules for generating programs from the context.
7.3. The Goal As said before, by planning space, one can prevent the waste of resources allowing, at the same time, to maximize the satisfaction of population needs. Planning plays, therefore, a key role in spatial and social organization (D. Harvey 2009). First, because it defines objectives that clarify the mission of the territory, and second because it establishes levels of effectiveness and efficiency by implementing measures to attain defined goals (Drucker 2007). A computational platform, here expressed by an ontology, facilitates the creation and the management of such a more complex planning instrument. With the ontology sketch was thus possible to classify the core entities of the planning domain knowledge, as well as set up a strategy to assess to its inconsistencies as well as reasoning the model. By undertake this first step towards the ontology building it was possible to define the strategy to implement the planning instrument in a more accurate, flexible and open process.
7.4. The Model According to what was said above, it is important to guarantee that the theories on which the proposed model is based are theoretically sound and meet to the desired goal. The academic theories used as a basis for this study are threefold: are well-known. The first one is Duarteâ&#x20AC;&#x2122;s model for the mass customization of housing (2001), upon which the formulation conceptual model was developed. Its premises are focused on context, interpretation, and formulation. The contribution of this model is to provide the technical
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apparatus, which is based on Stiny’s description and shape grammars and permits to link contextual descriptions to programmatic descriptions and then these to design outcomes. The second theory is the notion of pattern language proposed by Christopher Alexander (1977), which launched the bases for a planning language theory. Alexander’s premises depart from linguistics theory, which defines language as a combinatorial and creative method of communication in different contexts, with clear instructions, and within a defined vocabulary. The aim for this language is to allow users to manipulate creatively its ingredients to develop an appropriate speech that is a design adequate to a given context. In planning, such characteristics are particularly useful for enabling a creative and flexible process. The third theoretical framework consists in the use of a computational data model – a computational ontology (Gruber & others 1995) – to describe the semantic relational data of a given domain in a systematic way, as well as the relations among such entities and their instances. This framework will be used to describe both urban space and the urban planning process, thereby defining the formulation model.
7.5. The Outcome This research has provided the elaboration of the skeleton of the pre-design framework. This means that its components were developed and combined, and the methods to define its structure had also been implemented. The product of this research is therefore the development of the basic concepts of the formulation model, its methodology, its components, and the way data is manage to harness good results upon its future implementation. Other relevant and complimentary outcomes are the development of an ontology to support urban descriptions and the development of a tentative pattern language, adequate to the Western cultural context, that revises and complements Alexander’s pattern language. Together, the proposed ontology and pattern language will constitute the basis for future research, concerned with the inference of rules to link contextual features to programmatic descriptions.
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7.6. Reflections for future research A large part of this study is dedicated to the discovery of the most appropriate methodologies and tools to intervene in urban space with the objective of producing better living conditions for populations. However one cannot disregard that formulation in its primordial concept is far ahead from the definition of methods and techniques. An important concern pointed out in several chapters of this research is the necessity of taking into account placesâ&#x20AC;&#x2122; particularities and citizenâ&#x20AC;&#x2122;s aspirations (inhabitants and visitors) as they are the users of cities. Emphasizing this concern site interventions are increasingly more global and homogeneous both in terms of program and design proposal. She refers that in addition to local and global marketing strategies there is today an array of mandatory regulations and communitarian directives concerning patrimonial values, accessibilities, security and public sanitation, among other aspects, that are leading towards a gradual standardization of public spaces. One can also argue that portions of cities are drawn as finished objects, places without a future anima, in a sort of a perfect city scale model. In contrast, our research aims at urban planning strategies that can incorporate the desires and expectations of citizens. Quite often today, spaces are created where the urgency of consumption and the hyperprogramming constrain free choice. Urban programs will thus have to leave room for natural processes of urban evolution to take place in order to avoid the excesses of prescriptive or mandatory policies. They should be formulated in ways that define flexible rather than rigid specifications to enable unexpected while creative transformations along time. This goal constitutes a relevant focus of the developed model. Flexibility is considered, since the beginning of this study, as a core feature of urban programs and design proposals alike. One fact seems to be clear. The ontological framework is essential to build the data model. However crucial questions still require further clarification, namely: what quantity or quality of information is necessary to embed in the model? Furthermore where does it come from? In operational terms one can argue that the ontology editor will solve a large part of the data structure. However, how does one detail the ontology93? Will one simply seat in front of
93. The development of the model.
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the computer and develop the modelâ&#x20AC;&#x2122;s concepts and relations based on personal experience? If such happens, where will one search for the information that one does not possess yet? To answer to this question is, in summary, to explain the methodology of future research. In fact, it is possible to collect a great amount of relevant data through literature reviews or by undertaking additional methods and experiences. The brief conclusion is that the use of an ontology editor seems to be insufficient to eliminate all the expectable inconsistencies. The model has, thus, to be built using additional sources and methods.
7.7. The Opportunity There is one concept concerned with the description of building components and associated information that can provide a useful reference of the development of the urban formulation model. This concept is known as BIM. In summary, Building Information Models (BIM)94 comprise a system that aims at incorporating all aspects of design from geographic information, to building geometry, to component relationships, and finally, to the quantities and properties of the building components. BIM requires a purpose-built foundation to manage the amount of data generated. Such a description closely corresponds to the Urban Pattern Language (UPL) framework. The idea is depart from this correspondence to build a similar relational model, comprising a wide range of data to describe urban space and its properties. Such a City Information Model (CIM), 94 . Building Information Modeling is the process of generating and managing building data during its life cycle. Typically it uses three-dimensional, real-time, dynamic building modeling software to increase productivity in building design and construction. The process produces the Building Information Model (also abbreviated BIM), which encompasses building geometry, spatial relationships, geographic information, and quantities and properties of building components. Building information modeling covers geometry, spatial relationships, light analysis, geographic information, quantities and properties of building components (for example manufacturers' details). BIM can be used to demonstrate the entire building life cycle, including the processes of construction and facility operation. Quantities and shared properties of materials can be extracted easily. Scopes of work can be isolated and defined. Systems, assemblies and sequences can be shown in a relative sc ale with the entire facility or group of facilities. BIM can be seen as a companion to PLM as in the Product Development domain, since it goes beyond geometry and addresses issues such as Cost Management, Project Management and provides a way to work concurrent on most aspects of building life cycle processes. BIM goes far beyond switching to a new software. It requires changes to the definition of traditional architectural phases and more data sharing than most architects and engineers are used to. BIM is able to achieve such improvements by modeling representations of the actual parts and pieces being used to build a building. This is a substantial shift from the traditional computer aided drafting method of drawing with vector file-based lines that combine to represent objects.
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however, will have a wider semantic core and model hundreds of thousands of components more, when compared to the BIM and so it will represent a significantly more complex challenge. The goal of future research is to overcome such hurdles and develop such model.
Glossary
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Introduction Towards building an ontology is crucial the access to a common and shared lexicon (part of the aim of the ontology theory). The description of technical terms related with this specific field facilitates the engagement of such framework. This glossary presents hence an urban planning data synopsis (urban management, design, language, and methods) based on sorted written documents, namely; ESRI's Dictionary of GIS Terminology (Kennedy 2001), (Gann et al. 2003), (Evans et al. 2007), (Moughtin et al. 2003), among other references. This glossary is intended to provide general assistance, not authoritative definitions of terms which are sometimes controversial or used with different meanings in different contexts, in order to facilitate an application of specific technical terms.
Terms ACCESSIBILITY: The ability of people to move round an area and to reach places and facilities, including elderly and disabled people, those with young children and those encumbered with luggage or shopping. ACCESSORY USE (a) (GIS): The use of a building, structure or land that is subordinate to, customarily incidental to, and ordinarily found in association with, a principal use, which it serves. ACCESSORY USE (b): A building or a usage of land that is additional to primary use. A garage apartment or granny flat located behind the main house is an example of an accessory use. ACTIVITY CENTER (a) (GIS): A community focal point providing for the combination, rather than scatteration, of general retail, service commercial, professional office, higher density housing, and appropriate public/quasi-public uses. ACTIVITY CENTER (b): A central area within a neighborhood or at the intersection of several neighborhoods, that serves as a formal and/or informal gathering place. An activity center can be a commercial area with a variety of different types of retail establishments, often with public open space, a formal park, or any area that promotes interaction with other people on a personal and impersonal level and is pedestrian-oriented. ACTIVE FRONTAGE: This refers to ground floors with windows and doors onto the street which create interest and activity. This normally means shopfronts but can include atriums and foyers. ACTION PLANNING: Participation techniques, including community planning weekends and Urban Design Action Teams (UDATs), which enable local people and invited teams of professionals to explore design ideas for particular areas over one or several days. ACTIVITY SPINE: Street or streets along which activity is concentrated. Activity Node: Concentration of activity at a particular point. ACRE (GIS): 43,560 square feet (about the size of a football field). ADAPTABILITY: The capacity of a building or space to be changed so as to respond to changing social, technological and economic conditions.
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AGRICULTURAL ASSESSMENT (GIS): A state program in which land used for agricultural purposes is assessed based on its value as agricultural land as opposed to a higher valuation. AREA APPRAISAL: An assessment of an areaâ&#x20AC;&#x2122;s land uses, built and natural environment, and social and physical characteristics. AREA MASTER PLAN OR AREA PLAN (GIS): Area Master Plans: Area master plans consist of a plan map along with supporting data, text and other maps. They provide specific recommendations on a planning area or sub-region basis on the environment, historic preservation, living areas, housing, commercial areas, employment areas, urban design, circulation, and transportation. ARCHITECTURE AND PLANNING CENTRE (UK): An institution which provides a focus for a range of activities and services (such as discussions, information, exhibitions, collaboration and professional services) relating to architecture and planning. ARTERIAL (GIS): A highway, usually within a 120-foot right-of-way, for through traffic with access controlled to minimize direct connections, usually divided and on a continuous route. AT-GRADE (GIS): Level for a road, building or other structure at the same grade or level as the adjoining property (as opposed to a depressed or elevated road, building or other facility). ATRIUM: A circulation space, normally in the centre of an office building. This is often a high space with a glass roof that is the reception space for the building and the vertical circulation AVERAGE DAILY TRAFFIC (ADT): The average number of vehicles passing a specified point on a highway during a 24hour period. BASE DISTRICT: A zoning district that establishes regulations governing land use and site development in a specific geographic area. Example: - A minimum lot size of 10,000 square feet, - A minimum lot width of 60 feet, - That the house covers no more than 35% of the lot, - That all of the improvements (the house, driveway, sidewalk, etc.) cover no more than 40% of the lot, - That the house be no taller than 35 feet, - That the house be at least 25 feet from the street front. BASIC PLAN: Phase 1 of the Comprehensive Design Zone process. It sets forth general land use relationships, including the approximate number of dwelling units and building intensity. Proposed land uses are also described. BERM: An earthen mound designed to provide visual interest on a site, screening of undesirable views, noise reduction, etc. BEST MANAGEMENT PRACTICES (BMPs): Conservation practices or systems of practices and management measures that control soil loss and reduce water quality degradation caused by nutrients, animal waste, toxins and sediment. BIKEWAY: A lane, path or other surface reserved exclusively for bikers. BRIEF: This guide refers to site-specific briefs as development briefs. Site-specific briefs are also called a variety of other names, including urban programs, planning briefs and development frameworks. BUILDING LINE: The primary front face of buildings along a street. Where all of the buildings share a common building line (which can be curved) there is continuous enclosure along the street. BUILDING ELEMENTS: Doors, windows, cornices and other features which contribute to the overall design of a building. BUILDING ENVELOPE GUIDELINES: Diagram(s) with dimensions showing the possible site and massing of a building. BUILDING EXPLORATORY: A centre for explaining, interpreting and providing information on the built environment. BUILDING LINE: The line formed by the frontages of buildings along a street. The building line can be shown on a plan or section.
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BUFFER (a): An area of land designed or managed for the purpose of separating and insulating two or more land areas whose uses conflict or are incompatible (trees separating homes from an expressway). BUFFER (b) OR BUFFER STRIP: Landscaped areas, open spaces, fences, walls, berms, or any combination of these, used to physically separate or screen one land use or piece of property from another. Buffers are often used to block light or noise. BUFFERYARD: One of several specific combinations of minimum building setbacks, landscaped yard widths, and plant material requirements set forth in the Landscape Manual for use in buffering incompatible land uses. BUILT ENVIRONMENT: The urban environment consisting of buildings, roads, fixtures, parks, and all other improvements that form the physical character of a city. BULK: The combined effect of the arrangement, volume and shape of a building or group of buildings. Also called massing. BUS RAPID TRANSIT (BRT) (GIS): A fixed guideway transit (FGT) system in which transit buses operate on rights-ofway that are physically or otherwise off-limits to regular vehicular traffic. These systems are often constructed so that they can be upgraded to light-rail vehicle operations when ridership grows beyond the operational capacity of transit buses. CHARACTER: The image and perception of a community as defined by its built environment, landscaping, natural features and open space, types and style of housing, and number and size of roads and sidewalks. CHARACTER ASSESSMENT: An area appraisal identifying distinguishing physical features and emphasising historical and cultural associations. COMPATIBILITY STANDARDS: Development regulations established to minimize the effects of commercial, industrial, or intense residential development on nearby residential property. These standards usually include: Regulation of building height - Minimum and maximum building setbacks - Buffers - Building design - Controls to limit the impact of lighting on adjacent properties COMPREHENSIVE PLAN: A document, or series of documents, that serves as a guide for making land use changes, preparation of capital improvement programs, and the rate, timing, and location of future growth. It is based upon establishing long-term goals and objectives to guide the future growth of a city. It is also known as a Master or General Plan. Elements of a Comprehensive Plan include: - Economic Development - Environment Housing - Land Use - Recreation and Open Space - Transportation. CONTEXT: The setting of a site or area, including factors such as traffic, activities and land uses as well as landscape and built form. CONTEXT CONDITION (Language): Constrains the syntax; it describes the set of wellformed expressions of a language. CONTEXT (or site and area) APPRAISAL: A detailed analysis of the features of a site or area (including land uses, built and natural environment, and social and physical characteristics) which serves as the basis for an urban design framework, development brief, design guide or other policy or guidance. COUNTRYSIDE DESIGN SUMMARY: Supplementary planning guidance prepared by a local authority to encourage a more regionally and locally based approach to design and planning. CLUSTER DEVELOPMENT (GIS): An alternative development technique under zoning and subdivision regulations. A cluster subdivision is basically one in which a number of residential lots are grouped or clustered, leaving some land undivided for common use. Generally the same number of lots or dwelling units permitted under conventional subdivision procedures are clustered on smaller-than-usual lots. The land remaining from lot reduction is left undivided and is available as common area or open space. COMMUNITY ACTIVITY CENTER (GIS) (as defined in Master Plans): A commercial center containing 10-25 acres of commercial development on a site area of 20-30 acres, serving a population of at least 50,000 and anchored by a
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general merchandise store and may also include a supermarket. A community activity center should also include other commercial, public/quasi-public and residential uses. COMMUNITY CENTERS (GIS): Concentration of activities, services and land uses that serve, and are focal points for, the immediate neighborhoods. COMMUNITY (as defined in some master plans): A grouping of neighborhoods and villages, the population of which may range from 23,000 to 30,000 in suburban areas and up to 40,000 in corridor communities. Most communities should have as their centers of focal points a Community Activity Center. CONSTRAINED LONG-RANGE PLAN (CLRP) (GIS): The approved regional plan for highway, transit, and bikeway projects, as well as major jurisdictional and regional studies. CORRIDOR(S) (GIS): An uninterrupted path or channel of developed or undeveloped land paralleling the route of a street or highway. b. The land within one-quarter mile of both sides of designated high-volume transportation facilities, such as arterial roads. If the designated transportation facility is a limited access highway, the corridor extends one-quarter mile from the interchanges. CRIME PATTERN ANALYSIS: Carried out by the Police and is available through liaison with the Architectural Liaison Officer/Crime Prevention Design Adviser. It comprises four components: crime series identification, trend identification, “hot-spot” analysis and general profile analysis. This last aspect includes an examination of demographic and social change and its impact on criminality and law enforcement. DEFENSIBLE SPACE: Public and semi-public space that is “defensible” in the sense that it is surveyed, demarcated or maintained by somebody. Derived from Oscar Newman’s 1973 study of the same name, and an important concept in securing public safety in urban areas, defensible space is also dependent upon the existence of escape routes and the level of anonymity which can be anticipated by the users of the space. DENSITY (a): dph - Dwellings per hectare. DENSITY (b): The floorspace of a building or buildings or some other unit measure in relation to a given area of land. Built density can be expressed in terms of plot ratio (for commercial development); number of units or habitable rooms per hectare (for residential development); site coverage plus the number of floors or a maximum building height; or a combination of these. DENSITY (c): A measure of the amount of housing in a particular area (acre or a hectare). The simplest measure of density is the number of residential units per hectare which ranges for 30u/ha in a suburban area to 200u/ha or more in a city centre. Density can also be measured using habitable rooms or bed spaces which takes account of the type of units. DENSITY (d) (GIS): The number of dwelling units or persons per acre of land, usually expressed in units per gross acre. Single-family detached dwellings (range from less than 1 to 6 per acre) on a single lot. Townhouses (range from 6 to 12 per acre) attached in a row. Multifamily Apartments (range from 12 to 48 per acre) in one structure. DESIGN ADVISORY PANEL: A group of people (often architects) with specialist knowledge, which advises a local authority on the design merits of planning applications or other design issues. Also known as an architect’s panel. DESIGN ASSESSMENT: An independent assessment of a design usually carried out for a local authority by consultants, another local authority or some other agency. DESIGN GUIDE: A document providing guidance on how development can be carried out in accordance with the design policies of a local authority or other organisation often with a view to retaining local distinctiveness. DESIGN PRINCIPLE: An expression of one of the basic design ideas at the heart of an urban design framework, design guide, development brief or a development. DESIGN STANDARDS: Specific, usually quantifiable measures of amenity and safety in residential areas.
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DESIGN STATEMENT (a): A pre-application design statement is made by a developer to indicate the design principles on which a development proposal in progress is based. It enables the local authority to give an initial response to the main issues raised by the proposal. (b) A planning application design statement sets out the design principles that the planning applicant has adopted in relation to the site and its wider context, as required by PPG1. DESIRE LINE: An imaginary line linking facilities or places which people would find it convenient to travel between easily. DEVELOPMENT BRIEF: A document, prepared by a local planning authority, a developer, or jointly, providing guidance on how a site of significant size or sensitivity should be developed. Site-specific briefs are sometimes known as planning briefs, urban programs and development frameworks. DEVELOPMENT (as defined in Zoning Ordinance) (GIS): Any activity that materially affects the condition or use of dry land, land under water, or any structure. DOWNZONING (GIS): A popular term for an action that changes a property to a lower density, in effect limiting development to less-intense uses than previously permitted. DWELLING UNIT (GIS): A room or group of rooms, occupied or intended for occupancy as separate living quarters. ELEVATION (a): The facade of a building, or the drawing of a facade. ELEVATION (b): The front, back or side face of a building. ENCLOSURE: The use of buildings to create a sense of defined space. ENCLOSURE RATIO: A measure of the shape of a street expressed as a ratio in which the first number relates to the height of the buildings and the second to the width of the street. A street with an enclosure ratio of 1:2 is therefore twice as wide as the height of the buildings. ENERGY EFFICIENCY: The extent to which the use of energy is reduced through the way in which buildings are constructed and arranged on site. ENVIRONMENTAL IMPACT STATEMENT (EIS) (GIS): A document, prepared by a federal agency, on the environmental impact of its proposals for legislation and other major actions that significantly affect the quality of the human environment. Environmental Impact Statements are used as tools for decision making and are required by the National Environmental Policy Act. Similar environmental analyses are undertaken by state and local agencies. EYES OF THE STREET: Refers to views out of building that provide surveillance of public areas. EXPRESSION (Language): Is a meaningful, wellformed element of a language; the following are synonyms: word, statement, sentence, document, diagram, model, term, piece of data, clause, and module. FAĂ&#x2021;ADE: The front wall of a building. FEASIBILITY: The viability of development in relation to economic and market conditions. FENESTRATION: The arrangement of windows on a facade. DIAGRAM: A plan showing the relationship between built form and publicly accessible space (including streets) by presenting the former in black and the latter as a white background (or the other way round). FIXED GUIDEWAY TRANSIT (FGT): Transit service provided on its own right-of-way: a rail track, physically restricted vehicle lanes, or a dedicated roadway in the road and highway system. Both the Metrorail regional rapid transit and MARC commuter rail systems that serve Prince Georgeâ&#x20AC;&#x2122;s County are FGT systems. FLAG LOT (GIS): A flag-shaped lot, created under the Optional Residential Design Approach provisions of Subtitle 24, which has a street frontage smaller than that other required for the zone in which it is located.
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FLOATING ZONE (GIS): A zone that is more flexible than euclidean zones in terms of permissible densities, intensities and land uses and overall development design opportunities. Most floating zones require the following findings by the District Council to be granted: 1) The proposed zone is in conformance with the Master Plan; 2) Is compatible with the surrounding community; and 3) Meets the purposes of the zone. Findings of change or mistake, required for granting a euclidean zone, are not required for floating zones. Some floating zones require Master Plan recommendation. FLOODPLAIN (GIS): A relatively flat or lowland area adjoining a river, stream, or watercourse, which is subject to periodic, partial or complete inundation. FLOOR AREA RATIO (FAR): The ratio of the gross floor area of a building to the area of the lot on wich it is located. FORECAST (GIS): As defined for use in the Council of Governments (COG) Cooperative Forecasting Program, a projection tempered by stated policy considerations, including the reconciliation of past and current trends with current and future policies. Ideally, forecasts reflect the best professional judgment concerning the impact of trends and present conditions on the future trend of development and the likely effectiveness of policies to alter this trend. Therefore, forecasts should represent the most realistic assessment of the future. FORM: The layout (structure and urban grain), density, scale (height and massing), appearance (materials and details) and landscape of development. Frontage: Similar to facade - the front face of a building where it has its main door windows. FRUIN ANALYSIS: A method of analysing pedestrian movement devised by Bernard Fruin. It applies a “level of service” concept to pedestrian flows. Fruin defined capacity and speeds of movement in various forms of corridors, pavements and other pedestrian routes. FUTURE SEARCH: A participation technique enabling groups of people to identify common interests, discuss ideas and share information and experience. “Open space” is a similar technique. GEOGRAPHIC INFORMATION SYSTEM (GIS): An organized collection of computer hardware, software and geographic data designed to efficiently capture, store, update, manipulate, analyze and display all forms of geographically referenced information. GREEN AREA (GIS): An area of land associated with, and located on the same parcel of land as, a building for which it serves to provide light and air, or scenic, recreational, or similar purposes. GREEN BUILDING: Practices that consider the impacts of buildings on the local, regional, and global environment, energy and water efficiency, reduction of operation and maintenance costs, minimization of construction waste, and eliminating the use of harmful building materials. GREENWAYS: Areas of protected open space that follow natural and manmade linear features for recreation, transportation and conservation purposes and link ecological, cultural and recreational amenities. GRAIN (b): The complexity and coarseness of an urban area. Fine grained areas have a large number of different buildings and closely spaces streets. Course grained areas have large blocks and building and little architectural variety. GROSS FLOOR AREA (GFA): The total number of square feet of floor area in a building. HEIGHT: The height of a building can be expressed in terms of a maximum number of floors; a maximum height of parapet or ridge; a maximum overall height; any of these maximum heights in combination with a maximum number of floors; a ratio of building height to street or space width; height relative to particular landmarks or background buildings; or strategic views. HIGH-OCCUPANCY VEHICLE (HOV): A passenger vehicle containing more than one person. HOV facilities—such as John Hanson Highway (US 50) in Prince George’s County—generally require a minimum number of occupants for a vehicle to be granted access to HOV lanes.
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HIGH STREET: Traditionally a high street is a road through the heart of an urban area that carries all of the through traffic and is also where the greatest number and most important shops are sited together with civic functions. These streets would once have been the “shopfront” of the town or city. Now bypasses often mean that they no longer carry traffic but they do still tend to be the focus for the shopping area. HUMAN SCALE: The use within development of elements which relate well in size to an individual human being and their assembly in a way which makes people feel comfortable rather than overwhelmed. IDENTITY: The memorability or sense of place on an urban area. An area with identity is recognisable and has a distinctive character created by the size, shape or design of the buildings. IN-CURTILAGE PARKING: Parking within a building’s site boundary, rather than on a public street or space. INDEPENDENT DESIGN AUDIT: An assessment of a design, carried out for a local authority by consultants, another local authority or some other agency. INDICATIVE SKETCH: A drawing of building forms and spaces which is intended to convey the basic elements of a possible design. INTERPRETATION (Language): Extracts the information from a piece of data; it is a mapping of data to a semantic domain. LANDMARK: A building or structure that stands out from its background by virtue of height, size or some other aspect of design. LANDSCAPE: The character and appearance of land, including its shape, form, ecology, natural features, colours and elements and the way these components combine. Landscape character can be expressed through landscape appraisal, and maps or plans. In towns “townscape” describes the same concept. LAND USE (OR USE) (GIS): The types of buildings and activities existing in an area or on a specific site. Land use is to be distinguished from zoning, the latter being the regulation of existing and future land uses. LANGUAGE: Is a possibly infinite set of expressions used to communicate; it is a synonym to notation; a language allows us to syntactically represent information. LAYOUT: The way buildings, routes and open spaces are placed in relation to each other. LAYOUT STRUCTURE: The framework or hierarchy of routes that connect in the local area and at wider scales. LEGIBILITY: The degree to which a place can be easily understood and traversed. LIVE EDGE: Provided by a building or other feature whose use is directly accessible from the street or space which it faces; the opposite effect to a blank wall. LOCAL DISTINCTIVENESS: The positive features of a place and its communities which contribute to its special character and sense of place. LYNCHIAN ANALYSIS: The widely used method of context appraisal devised by the urban designer Kevin Lynch. It focuses on gateways to an area, nodes, landmarks, views and vistas, and edges and barriers. MAJOR COMMUNITY ACTIVITY CENTER (as defined in master plans): A commercial center containing 20-50 acres of commercial development on a site area of 30-60 acres, serving a population of at least 150,000. A major community activity center typically includes uses listed under community activity center plus one or more general merchandise anchor stores. Can also be defined as a community focal point providing for a concentration of activities such as general retail, service commercial, professional office, higher-density housing, and appropriate public and open space uses easily accessible by pedestrians. MANDATORY (LAND) DEDICATION (GIS): Land excluded from subdivision approved for residential development. The land is dedicated to M-NCPPC (or held in private ownership) for the purpose of providing suitable and adequate open space, light, and air to serve the recreational needs of the future occupants of the subdivision.
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MASTER PLAN: A document that guides the way an area should be developed. It includes a compilation of policy statements, goals, standards, maps and pertinent data relative to the past, present, and future trends of a particular area of the County including, but not limited to, its population, housing, economics, social patterns, land use, water resources and their use, transportation facilities, and public facilities. MASSING (a): The size and height of a building. MASSING (b): The combined effect of the height, bulk and silhouette of a building or group of buildings. MIXED USE (MU): A type of development that combines residential, commercial, and/or office uses, within a commercial or office zoning district, into one development or building. For example, a mixed-use building could have several floors. On the bottom floor, the space could be dedicated to retail or offices. The remaining two or three floors could be for apartments or condominiums. A Mixed Use Combining District allows residential, commercial, retail, and office uses to be combined in a single development. Under the Smart Growth Infill Ordinance two types of Mixed Use development are now possible with adopted neighborhood plans that include these uses as part of their plans: - Neighborhood Urban Center allows a variety of residential types (condos, apartments, townhouses) and commercial, office, and retail uses clustered together in a development of less than forty acres. - A Neighborhood Mixed Use Building allows residential uses above ground floor commercial uses. Multi-Family: A building that is designed to house more than one family. MIXED USES: A mix of uses within a building, on a site or within a particular area. “Horizontal” mixed uses are side by side, usually in different buildings. “Vertical” mixed uses are on different floors of the same building. MIXED-USE ZONING (GIS): Zoning that permits a combination of uses within a single development. Many zoning districts specify permitted combinations of, for example, residential and office/commercial uses. The term has also been applied to major developments, often with several high-rise buildings, that may contain offices, shops, hotels, apartments and related uses. MODAL SPLIT: How the total number of journeys in an area or to a destination is split between different means of transport, such as train, bus, car, walking and cycling. MODELLING LANGUAGE (Language): Is used for specifying and documenting properties of a system in different abstractions, and from different points of view. MOVEMENT: People and vehicles going to and passing through buildings, places and spaces. The movement network can be shown on plans, by space syntax analysis, by highway designations, by figure and ground diagrams, through data on origins and destinations or pedestrian flows, by desire lines, by details of public transport services, by walk bands or by details of cycle routes. NATURAL SURVEILLANCE (or supervision): The discouragement to wrong-doing by the presence of passers-by or the ability of people to be seen out of surrounding windows. Also known as passive surveillance (or supervision). NEIGHBORHOOD: (As defined in some master plans) The smallest unit of community structure. Neighborhood population ranges from 3,000 to 6,000, depending on the ratio of single-family to multifamily housing. NEIGHBORHOOD CONVENIENCE CENTER (as defined in master plans): A commercial center containing 2-6 acres of commercial development on a site of 4-10 acres, serving a population of approximately 8,000 and anchored by a small grocery or drug store. It should also include a limited range of other commercial and residential uses. NET LOT AREA (GIS): The total contiguous area included within a lot, excluding public ways (i.e., streets, alleys) and land with 100-year floodplain. NODE (GIS): A location along a corridor at a major intersection or major transit stop (bus or rail) that consists of a concentration of high-intensity, mixed-use residential and commercial development. Nodes should be interspersed with stretches of lower intensity land uses or open space. NODE: A place where activity and routes are concentrated often used as a synonym for junction.
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NOTATION (Language): Is a syntactic representation of information; a synonym to language; what the user deals with. OPEN SPACE (a) (land use, not zoning) (GIS): Areas of land not covered by structures, driveways, or parking lots. Open space may include homeowners association common areas, parks, lakes, streams and ponds, etc. OPEN SPACE (b): An area set aside or reserved for public or private use with very few improvements. Types of open space include include:- Golf Courses- Agricultural Land- Parks- Greenbelts- Nature Preserves. In many cases, land designated as open space lies within the 100-year flood zone, has sensitive environmental features such as wetlands or aquifer recharge features such as caves and fault lines, or has unstable slopes. PASSIVE SURVEILLANCE: See â&#x20AC;&#x153;natural surveillanceâ&#x20AC;?. PEDESTRIAN-ORIENTED DESIGN (GIS): Land use activities that are designed and arranged in a way that emphasizes travel on foot rather than by car. The factors that encourage people to walk are often subtle, but they most regularly focus upon the creation of a pleasant environment for the pedestrian. Elements include compact, mixeduse development patterns with facilities and design that enhance the environment for pedestrians in terms of safety, walking distances, comfort, and the visual appeal of the surroundings. Pedestrian-friendly environments can be created by locating buildings close to the sidewalk, by lining the street with trees, and by buffering the sidewalk with planting strips or parked cars, small shops, street-level lighting and signs, and public art or displays. PERFORMANCE CRITERION (pl. criteria): A means of assessing the extent to which a development achieves a particular functional requirement (such as maintaining privacy). This contrasts with a standard, which specifies how a development is to be designed (by setting out minimum distances between buildings, for example). The art of urban design lies in balancing principles which may conflict. Standards may be too inflexible to be of use in achieving a balance. Performance criteria, on the other hand, make no prior assumptions about the means of achieving a balance. PERMEABILITY (a): The degree to which an area has a variety of pleasant, convenient and safe routes through it. PERMEABILITY (b): The ease with which people can move around an urban area. A permeable neighbourhood has plenty of streets and it is possible to move through the area by a variety of routes. PERSPECTIVE: Illustration showing the view from a particular point as it would be seen by the human eye. PLACECHECK: A type of urban design audit advocated by the Urban Design Alliance, based on the Connected City approach. A local collaborative alliance or partnership uses checklists to investigate the connections in the built environment, in its movement network and among the people who shape it. The Placecheck becomes the first step in a continuing collaborative process of urban design. PLANNING: The process of setting development goals and policy, gathering and evaluating information, and developing alternatives for future actions based on the evaluation of the information. PLANNING BRIEF: This guide refers to site-specific briefs as development briefs. Other names, including planning briefs, urban programs and development frameworks are also used. PLANNING FOR REAL: A participation technique (pioneered by the Neighbourhood Initiatives Foundation) that involves residents and others with an interest coming together to make a model of their area and using it to help them determine their priorities for the future. PLANNING POLICY GUIDANCE NOTES (PPGs): Documents embodying Government guidance on general and specific aspects of planning policy to be taken into account in formulating development plan policies and in making planning decisions. PLOT RATIO (a): A measurement of density generally expressed as gross floor area divided by the net site area. PLOT RATIO (b): A measure of density for non-residential used. This is expressed as a ratio in which the first number relates to the floor area of the building and the second to the area of the site. A 2:1 ratio therefore denotes a
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building that has two times the floor area of the site. This could be a two storey building covering the entire site or a four storey building covering half of the site. PRIVACY DISTANCE: The distance between the habitable windows of a dwelling necessary to ensure privacy. This is normally 20-23m but can be reduced to 15m in city centres. Where a dwelling has a front on a back the privacy distance relates to the back. On double-loaded flats (see above) it relates to the front. PROACTIVE DEVELOPMENT CONTROL: Any process by which a local authority works with potential planning applicants to improve the quality of development proposals as early as possible before a planning application is submitted. PROGRAMMING LANGUAGE (Language): Is used for programming software systems. PUBLIC ART: Permanent or temporary physical works of art visible to the general public, whether part of the building or free-standing: can include sculpture, lighting effects, street furniture, paving, railings and signs. PUBLIC DOMAIN: The parts of a village, town or city (whether publicly or privately owned) that are available, without charge, for everyone to use or see, including streets, squares and parks. Also called public realm. PUBLIC/PRIVATE INTERFACE: The point at which public areas PUBLIC REALM: The public spaces of an urban area. This includes streets, squares and parks where people are free to walk. It does not include private gardens or courtyards or shopping malls. SEMANTICS (Language): Defines the meaning of a notation; what information do the expressions in the notation describe. SEMANTIC DOMAIN (Language): Is a well understood domain of elements. Elements of the semantic domain describe the important properties of what we are trying to define using a language in our context; this means software and hardware systems, and components of such systems. SEMANTIC MAPPING (Language): Is a mapping that relates each syntactic construct to a construct of the semantic domain; it usually explains new constructs in terms of known constructs. SETBACK: The distance between a building or structure (not including ground-level parking lots or other paved surfaces) from property lines or from other buildings. SEVERE SLOPES: Those slopes that are greater than 25 percent. (Example: a 25-foot change in elevation in a 100foot horizontal distance.) SITING: The positioning of a building on the ground. SMART GROWTH: A perspective, method, and goal for managing the growth of a community. It focuses on the longterm implications of growth and how it may affect the community, instead of viewing growth as an end in itself. The community can vary in size; it may be as small as a city block or a neighborhood, or as large as a city, a metropolitan area, or even a region. Smart Growth promotes cooperation between often diverse groups to arrive at sustainable long-term strategies for managing growth. It is designed to create livable cities, promote economic development, and protect open spaces, environmentally sensitive areas, and agricultural lands. SMART HOUSING: An initiative of the City of Austin to promote sustainable and equitable housing development for low- to moderate-income households. Housing developed under this program would serve the needs of a variety of income levels and be accessible to people with disabilities. The SMART Housing Initiative also requires that housing developed under the program have ready access to transit. SMART stands for: S
afe
M
ixed-Incom
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A
accessible
R
easonably Priced
T
ransit-oriented
SPECIFIC DESIGN PLAN (SDP): Phase III of the Comprehensive Design Zone process. It is a precise site plan that includes exact locations of lots, buildings and streets, etc., architectural plans, exterior building elevations and detailed landscaping plans. SPRAWL: A haphazard and disorderly form of urban development. There are several elements that characterize sprawl: - Residences far removed from stores, parks, and other activity centers, - Scattered or “leapfrog” development that leaves large tracts of undeveloped land between developments, - Commercial strip development along major streets, - Large expanses of low-density or single use development such as commercial centers with no office or residential uses, or residential areas with no nearby commercial centers, - Major form of transportation is the automobile, - Uninterrupted and contiguous low- to medium-density (one to six du/ac) urban development, - Walled residential subdivisions that do not connect to adjacent residential development.
STAR BUILDING: This relates to a building that is special by virtue of its role. Traditionally this would include churches, town halls and other public institutions. These buildings should be commissioned by public competition but are not subject to the same rules as other buildings. STREET HIERARCHY: The relative importance of different streets. This traditionally includes high streets that carry most through traffic and have the greatest number of shops, secondary streets that take traffic into each neighbourhood and have fewer shops and local streets that give access to each of the buildings. Today high streets are often pedestrianised and through traffic is carried on a new level of the hierarchy - the boulevard. STREETSCAPE: The space between the buildings on either side of a street that defines its character. The elements of a streetscape include: - Building Frontage/Façade, - Landscaping (trees, yards, bushes, plantings, etc.), - Sidewalks, - Street Paving, - Street Furniture (benches, kiosks, trash receptacles, fountains, etc), - Signs, - Awnings, - Street Lighting. SUB-LANGUAGE (Language): Is a subset of the syntactic elements, together with an appropriate adaptation projection. SUSTAINABILITY: A concept and strategy by which communities seek economic development approaches that benefit the local environment and quality of life. Sustainable development provides a framework under which communities can use resources efficiently, create efficient infrastructures, protect and enhance the quality of life, and create new businesses to strengthen their economies. A sustainable community is achieved by a long-term and integrated approach to developing and achieving a healthy community by addressing economic, environmental, and social issues. Fostering a strong sense of community and building partnerships and consensus among key stakeholders are also important elements. SUPPORTING CAST BUILDING: This relates to the majority of buildings in an urban area - all of the housing, shops and offices. These create the urban form of an urban area and should be subject to urban design rules.
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TEXTUAL LANGUAGE (Language): Is a language consisting of linear strings of characters and symbols; words, sentences, etc. TRADITIONAL NEIGHBORHOOD CORRIDOR: The combination of an activity center and the transportation connections linking it to the rest of city. These links may be made by frequent public transit service, walking, cycling, or by car. The major throughway into a traditional neighborhood corridor should be wide enough to accommodate all modes of vehicular transportation, on-street parking, as well as provide space for safe and inviting sidewalks for pedestrians. A Traditional Neighborhood Corridor is characterized by a mixture of various uses and densities such as stores, offices, and different types of housing. TRANSIT-ORIENTED DEVELOPMENT (TOD): A form of development that emphasizes alternative forms of transportation other than the automobile - such as walking, cycling, and mass transit - as part of its design. TransitOriented Development locates retail and office space around a transit stop. This activity center is located adjacent to a residential area with a variety of housing options such as apartments, townhouses, duplexes, and single family houses. Similar to a Traditional Neighborhood Development. TRANSIT NODES: Stops along a public transportation route where people board and disembark, often where one or more routes intersect with each other. These sites can provide ideal locations for mixed use development as well as transit-oriented development. URBAN BLOCK: This is an area bounded by streets and occupied by buildings. Sometimes called a perimeter block, the buildings face outwards onto the streets often with a private courtyard in the centre. For housing development this courtyard is often used by residents (sometimes for gardens) for shops it is where servicing takes place and of offices it is often an atrium. VISUAL/DIAGRAMMATIC LANGUAGE (Language): Is a language based mainly on graphic (topological geometric) elements; it can employ textual elements too. VISUAL FORMALISM (Language): Is a diagrammatic language that has formal syntax and semantics. ZONING (a) (GIS): The classification of land by types of uses permitted and prohibited in a district and by densities and intensities permitted and prohibited, including regulations regarding building location on lots. ZONING (b): The method used by cities to promote the compatibility of land uses by dividing tracts of land within the city into different districts or zones. Zoning ensures that a factory is not located in the middle of a residential neighborhood or that a bar is not located next to an elementary school. ZONING CATEGORY or DISTRICT (GIS): An area designated (zoned) for a type of land use and for a certain density or intensity of development within that type. ZONING MAP (GIS): The official 1"=200' scale map showing the location of all zoning categories in a given area.
Conventions Some Conventions of Abbreviated terms in GIS, in Computer Aided Design, and in other languages. 2D: Two Dimensional 3D: Three Dimensional AEC: Architecture, Engineering, Construction ALKIS: German National Standard for Cadastral Information ATKIS: German National Standard for Topographic and Cartographic Information B-Rep: Boundary Representation
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CAD: Computer Aided Design CAAD: Computer Aided Architectural Design DTM: Digital Terrain Model DXF: Drawing Exchange Format FM: Facility Management GDF: Geographic Data Files GML: Geography Markup Language IAI: International Alliance for Interoperability IETF: Internet Engineering Task Force IFC: Industry Foundation Classes ISO: International Organization for Standardisation LOD: Level of Detail NBIMS: National Building Information Model Standard OASIS: Organisation for the Advancement of Structured Information Standards OGC: Open Geospatial Consortium OSCRE: Open Standards Consortium for Real Estate SIG 3D: Special Interest Group 3D of the GDI NRW TC211: ISO Technical Committee 211 TIC: Terrain Intersection Curve TIN: Triangulated Irregular Network UML: Unified Modeling Language URI: Uniform Resource Identifier VRML: Virtual Reality Modeling Language W3C: World Wide Web Consortium XML Extensible Markup Language
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Annexes
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Annex 1 A rule case-study edited by the Protégé rules editor Distance between buildings (Trento 2009) “Using an existing ontology and rules editor (Protegé2000 + PAL Constraints), authors implemented a design rule which states that each single family house (denominated “building”) must not be closer than 15 meters to another building (Figure). (...) By means of the purposed Knowledge Modelling level, this rule can be linked to the building entities involved in the design process and formalized in order to support the designers with some inferred suggestions. (...) The Goals and Constraints editing, through the described mechanism, allow the coherence of the design to be verified vis-à-vis the objective sets. The research in progress is revealing the potential of the approach adopted for the preliminary design phase representing a first-step validation of the illustrated software system implementation.”
9.
Design rule formalization on Protégé Axiom Language
Annex 2
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An example of an ontological class edition and its exported XML format Protégé ontologies can be exported into a XML Schema. In the bottom is shown the class hierarchy of climatic patterns ontology. At its bottom is shown the the XLM related Shema.
Ontology Class Hierarchy
10. Class edition on Protégé 2000
Ontology XML Schema <?xml version="1.0" ?> - <knowledge_base xmlns="http://protege.stanford.edu/xml" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://protege.stanford.edu/xml http://protege.stanford.edu/xml/schema/protege.xsd"> - <class> <name>:THING</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Abstract</value> </own_slot_value> </class> - <class> <name>:STANDARD-CLASS</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> <superclass>:CLASS</superclass> <template_slot>:ROLE</template_slot> <template_slot>:DOCUMENTATION</template_slot>
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<template_slot>:SLOT-CONSTRAINTS</template_slot> <template_slot>:ROLE</template_slot> <template_slot>:DOCUMENTATION</template_slot> <template_slot>:SLOT-CONSTRAINTS</template_slot> </class> - <class> <name>:STANDARD-SLOT</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> <superclass>:SLOT</superclass> <template_slot>:DOCUMENTATION</template_slot> <template_slot>:SLOT-CONSTRAINTS</template_slot> <template_slot>:SLOT-MAXIMUM-CARDINALITY</template_slot> <template_slot>:SLOT-MINIMUM-CARDINALITY</template_slot> <template_slot>:SLOT-NUMERIC-MAXIMUM</template_slot> <template_slot>:SLOT-NUMERIC-MINIMUM</template_slot> <template_slot>:SLOT-INVERSE</template_slot> <template_slot>:SLOT-DEFAULTS</template_slot> <template_slot>:SLOT-VALUES</template_slot> <template_slot>:ASSOCIATED-FACET</template_slot> <template_slot>:DIRECT-SUBSLOTS</template_slot> <template_slot>:DIRECT-SUPERSLOTS</template_slot> <template_slot>:DOCUMENTATION</template_slot> <template_slot>:SLOT-CONSTRAINTS</template_slot> <template_slot>:SLOT-MAXIMUM-CARDINALITY</template_slot> <template_slot>:SLOT-MINIMUM-CARDINALITY</template_slot> <template_slot>:SLOT-NUMERIC-MAXIMUM</template_slot> <template_slot>:SLOT-NUMERIC-MINIMUM</template_slot> <template_slot>:SLOT-INVERSE</template_slot> <template_slot>:SLOT-DEFAULTS</template_slot> <template_slot>:SLOT-VALUES</template_slot> <template_slot>:ASSOCIATED-FACET</template_slot> <template_slot>:DIRECT-SUBSLOTS</template_slot> <template_slot>:DIRECT-SUPERSLOTS</template_slot> </class> - <class> <name>Cold Region</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> <superclass>:THING</superclass> </class> - <class> <name>Election of the location</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> <superclass>Cold Region</superclass> </class> - <class> <name>Slopes</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Abstract</value> </own_slot_value> <superclass>Election of the location</superclass> </class>
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- <class> <name>Urban structure</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> <superclass>Cold Region</superclass> </class> - <class> <name>Public Spaces</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> <superclass>Cold Region</superclass> </class> - <class> <name>Landscape</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> <superclass>Cold Region</superclass> </class> - <class> <name>Vegetation</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> <superclass>Cold Region</superclass> </class> - <class> <name>Perish vegetation</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Abstract</value> </own_slot_value> <superclass>Vegetation</superclass> </class> - <class> <name>Persistent vegetation</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Abstract</value> </own_slot_value> <superclass>Vegetation</superclass> </class> - <class> <name>House Type</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> <superclass>Cold Region</superclass> </class> - <class> <name>General distribution</name>
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<type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> <superclass>Cold Region</superclass> </class> - <class> <name>Distribution Plan</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> <superclass>Cold Region</superclass> </class> - <class> <name>Form and volume</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> <superclass>Cold Region</superclass> <template_slot>Bioclimatic Pattern_Slot_0</template_slot> </class> - <class> <name>Orientation</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> <superclass>Cold Region</superclass> </class> - <class> <name>Color</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> <superclass>Cold Region</superclass> </class> - <slot> <name>Bioclimatic Pattern_Slot_0</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">String</value> </own_slot_value> </slot> - <slot> <name>:ASSOCIATED-FACET</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-INVERSE</slot_reference>
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<value value_type="slot">:ASSOCIATED-SLOT</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Instance</value> <value value_type="class">:FACET</value> </own_slot_value> </slot> - <slot> <name>:DIRECT-SUBSLOTS</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-INVERSE</slot_reference> <value value_type="slot">:DIRECT-SUPERSLOTS</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Instance</value> <value value_type="class">:SLOT</value> </own_slot_value> </slot> - <slot> <name>:DIRECT-SUPERSLOTS</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-INVERSE</slot_reference> <value value_type="slot">:DIRECT-SUBSLOTS</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Instance</value> <value value_type="class">:SLOT</value> </own_slot_value> </slot> - <slot> <name>:DOCUMENTATION</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:DOCUMENTATION-IN-FRAME</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">String</value> </own_slot_value> </slot> - <slot> <name>:ROLE</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-DEFAULTS</slot_reference> <value value_type="string">Concrete</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Symbol</value> <value value_type="string">Abstract</value> <value value_type="string">Concrete</value> </own_slot_value> </slot> - <slot>
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<name>:SLOT-CONSTRAINTS</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:CONSTRAINTS</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Instance</value> <value value_type="class">:CONSTRAINT</value> </own_slot_value> </slot> - <slot> <name>:SLOT-DEFAULTS</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:DEFAULTS</value> </own_slot_value> </slot> - <slot> <name>:SLOT-INVERSE</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-INVERSE</slot_reference> <value value_type="slot">:SLOT-INVERSE</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Instance</value> <value value_type="class">:SLOT</value> </own_slot_value> </slot> - <slot> <name>:SLOT-MAXIMUM-CARDINALITY</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-DEFAULTS</slot_reference> <value value_type="integer">1</value> </own_slot_value> - <own_slot_value> <slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:MAXIMUM-CARDINALITY</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Integer</value> </own_slot_value> </slot> - <slot> <name>:SLOT-MINIMUM-CARDINALITY</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value> </own_slot_value> - <own_slot_value>
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<slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:MINIMUM-CARDINALITY</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Integer</value> </own_slot_value> </slot> - <slot> <name>:SLOT-NUMERIC-MAXIMUM</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value> </own_slot_value> - <own_slot_value> <slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:NUMERIC-MAXIMUM</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Float</value> </own_slot_value> </slot> - <slot> <name>:SLOT-NUMERIC-MINIMUM</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value> </own_slot_value> - <own_slot_value> <slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:NUMERIC-MINIMUM</value> </own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Float</value> </own_slot_value> </slot> - <slot> <name>:SLOT-VALUES</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:VALUES</value> </own_slot_value> </slot> </knowledge_base>
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Annex 3
PEST Analysis Template Urban plan analyzed: ___________________________________________________________________
PEST analysis (political, economical, social, and technological) assesses a standpoint of a particular planâ&#x20AC;&#x2122;s proposition.
criteria examples
political
economical
a) Ecological/environmental current legislation b) Future legislation c) International legislation d) Regulatory bodies and processes e) Government policies f) Government term and change g) Urban codes h) Initiatives i) Home pressure- groups j) International pressuregroups k) Conflicts
criteria examples a) Lifestyle trends b) Demographics c) Social attitudes and opinions d) Media views e) Law changes affecting social factors f) Brand, company, technology image g) Fashion and role models h) Major events and influences i) Buying access j) Ethnic/religious factors k) Ethical issues
criteria examples a) Home economy b) Economy trends c) Overseas related economies d) General taxation e) Seasonality issues f) Market cycles g) Specific industry factors h) Interest
social
technological
criteria examples a) Competing technology development b) Research c) Associated/dependent technologies d) Replacement technology/solutions e) Maturity of technology f) Information and communications g) Technology legislation h) Innovation potential i) Technology access, licencing j) Intellectual property issues k) Global communications
11. PEST analysis Note: PEST analysis can be useful before SWOT analysis because PEST helps to identify SWOT factors. PEST and SWOT are two different perspectives but can contain common factors. SWOT stands for strengths, weaknesses, opportunities, threats.
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SWOT Analysis Template Urban plan analyzed: ___________________________________________________________________ This SWOT example is for a new urban plan. Many criteria can apply to more than one quadrant. Identify criteria appropriate to each specific SWOT situation.
criteria examples
strengths
weaknesses
Advantages of proposition? Capabilities? Competitive advantages? Resources, Assets? Knowledge, data? Innovative aspects? Location and geographical? Value, quality? Processes, systems, IT? Cultural, attitudinal, behavioural? Management? Philosophy and values?
criteria examples Territory developments? Social cohesion? Industry and lifestyle trends? Technology development and innovation? Economic development? Environmental concerns? Global influences? Competitors' vulnerabilities? Tactics: e.g., surprise? Information and research? Partnerships? Seasonal, weather, fashion influences?
criteria examples Disadvantages of proposition? Gaps in capabilities? Lack of competitive strength? Reputation, presence and reach? Financials? Own known vulnerabilities? Timescales, deadlines and pressures? Continuity, supply chain robustness? Effects on core activities, distraction? Reliability of data, plan predictability? Processes and systems? Management?
opportunities
threats
criteria examples Social unsteadiness? Political frame? Legislative effects? Environmental effects? Competitor intentions? IT developments? Market demand? New technologies, services, ideas? Obstacles faced? Insurmountable weaknesses? Sustainable financial backing? Economy? Seasonality, weather effects?
12. PEST analysis Initially develop by Alan Chapman 2005-09 (www.businessballs.com/swotanalysisfreetemplate.htm)
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Annex 4 Regulations and contextual data attributes, proposed codes, types, reference values, data sources, and related calculations (Gil 2009). Table of Building related attributes Attributes
Codes
Types
Number of inhabitants
HABN
Socioeconomic
Gross Floor Area
GFA
Socioeconomic
Built-up area
BA
Number of Floors
Refs
Sources
Calculations
1
Census/Plan
integer
5
Composite
BA * F
General
1,5
Geometry
m2
F
General
1,5
Survey/Plan
integer
Dwellings area
DWEA
Socioeconomic
7
Survey/Plan
m2
Number of Dwellings
DWEN
Socioeconomic
1
Survey/Plan
integer
Retail units area
RETA
Socioeconomic
7
Survey/Plan
m2
Number of Retail units
RETN
Socioeconomic
4,7
Survey/Plan
integer
Construction date
COND
Cultural
3,4
Census
year
Population Ethnic origin
POPE
Cultural
4
Census
% share
Population age
POPA
Socioeconomic
4
Census
% share
Population Socio-economic status
POPS
Socioeconomic
4,6
Census
% share
Exposure to prevailing winds
WNDE
Bioclimatic
2,3
Composite
m2
Shaded area
SHDA
Bioclimatic
2
Composite
m2
Solar Exposure
SOLE
Bioclimatic
2,3
Composite
SOLO - DIR
Dwellings proximity
DWEP
Socioeconomic
7
Composite
SUM DWEN (or DWEA)
Number of parking spaces per dwelling
PRKD
Socioeconomic
1
Composite
PRKN/DWEN
Retail units proximity
RETP
Socioeconomic
7
Composite
SUM RETN (or RETA)
Compactness
COM
Bioclimatic
2
Geometry
A/LEN
Length
LEN
General
2,4,6
Geometry
m
Proportion
PROP
Bioclimatic
2
Geometry
LEN/W
Orientation
DIR
General
2,4
Geometry
degrees
Exposure
EXP
General
2
Geometry
integer
Width
W
General
1,2,4
Geometry
m
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State of Conservation
CONS
Cultural
3,4
Survey/Plan
Attribute
Construction type
CONT
Cultural
3,4
Survey/Plan
Attribute
Typology
TYP
General
2
Survey/Plan
Attribute
Ground Floor use
GFU
Socioeconomic
4,6,7
Survey/Plan
%share
Upper floors use
UFU
Socioeconomic
6,7
Survey/Plan
%share
Surface quality
SURF
Bioclimatic
2
Survey/Plan
Attribute
Solar Orientation
SOLO
Bioclimatic
2,3
Weather Data
N,S,E,W
Table of Plot related attributes Attributes
Codes
Types
Green area
GREA
Bioclimatic
Common space area
COMA
Private space area
Refs
Sources
Calculations
2
Attribute/Geometry
m2
Socio-economic
1,4
Attribute/Geometry
m2
PRVA
Socio-economic
1,4
Attribute/Geometry
m2
Public space area
PUBA
Socio-economic
1,4
Attribute/Geometry
m2
Shaded area
SHDA
Bioclimatic
2
Composite
m2
Dwellings density
DWED
Socio-economic
1
Composite
DWEN/A
Floor Area Ratio or Floor Space Index
FAR or FSI
Socio-economic
5
Composite
GFA / TA
Mean number of floors
FAVG
Socio-economic
1
Composite
FSUM/BLDN
Mode number of floors
FMOD
Socio-economic
1
Composite
Mode F
Ground Space Index
GSI
Socio-economic
1,5
Composite
BA / TA
Layers
L
Socio-economic
5
Composite
GFA/BA
Open Space Ratio
OSR
Socio-economic
5
Composite
(TA - BA) / GFA
Retail units density
RETD
Socio-economic
7
Composite
RETN/A
Exposure
EXP
General
2
Geometry
integer
Width
W
General
1,2,4
Geometry
m
Area
TA
General
1,5
Geometry
m2
Attributes
Codes
Types
Refs
Sources
Calculations
Length
LEN
General
2,4,6
Geometry
m
Orientation
DIR
General
2,4
Geometry
degrees
Width
W
General
1,2,4
Geometry
m
Area
TA
General
1,5
Geometry
m2
Table of Block related attributes
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Floor Area Ratio or Floor Space Index
FAR or FSI
Socio-economic
5
Composite
GFA / TA
Mean number of floors
FAVG
Mode number of floors
FMOD
Socio-economic Socio-economic
1 1
Composite Composite
FSUM/BLDN Mode F
Ground Space Index
GSI
Socio-economic
1,5
Composite
BA / TA
Layers
L
Socio-economic
5
Composite
GFA/BA
Open Space Ratio
OSR
Socio-economic
5
Composite
(TA - BA) / GFA
Number of Buildings
BLDN
Socio-economic
1
Geometry
integer
Built-up area
BA
General
1,5
Geometry
m2
Proportion
PROP
Bioclimatic
2
Geometry
LEN/W
Solar Orientation
SOLO
Bioclimatic
2,3
Geometry
N,S,E,W
Green area
GREA
Bioclimatic
2
Attribute/Geometry
m2
Common space area
COMA
Socio-economic
1,4
Attribute/Geometry
m2
Private space area
PRVA
Socio-economic
1,4
Attribute/Geometry
m2
Public space area
PUBA
Socio-economic
1,4
Attribute/Geometry
m2
Dwellings total
RETT
Socio-economic
6
Composite
SUM DWEN (or DWEA)
Retail units total
RETT
Socio-economic
6
Composite
SUM RETN (or RETA)
Dwellings density
DWED
Socio-economic
1
Composite
DWEN/A
Retail units density
RETD
Socio-economic
7
Composite
RETN/A
Number of inhabitants
HABN
Socio-economic
1
Census/Plan
integer
Exposure to prevailing winds
WNDE
Bioclimatic
2,3
Composite
m2
Shaded area
SHDA
Bioclimatic
2
Composite
m2
Pavement width
PAVW
Socio-economic
1
Geometry
m
Vegetation type
VEG
Bioclimatic
2
Survey/Plan
%share
Number of parking spaces
PRKN
Mobility
1
Survey/Plan
integer
Table of Street related attributes Attributes
Codes
Types
Refs
Sources
Calculations
Orientation
DIR
General
2,4
Geometry
degrees
Length
LEN
General
2,4,6
Geometry
m
Width
W
General
1,2,4
Geometry
m
Solar Orientation
SOLO
Bioclimatic
2,3
Weather Data
N,S,E,W
Solar Exposure
SOLE
Bioclimatic
2,3
Composite
SOLO - DIR
Number of Buildings
BLDN
Socio-economic
1
Geometry
integer
Pavement width
PAVW
Socio-economic
1
Geometry
m
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Proportion
PROP
General
2
Geometry
LEN/W
Pedestrian area
PEDA
Mobility
1
Attribute/Geometry
m2
Common space area
COMA
Socio-economic
1,4
Attribute/Geometry
m2
Private space area
PRVA
Socio-economic
1,4
Attribute/Geometry
m2
Public space area
PUBA
Socio-economic
1,4
Attribute/Geometry
m2
Vehicular area
VEHA
Mobility
1
Attribute/Geometry
m2
Dwellings total
RETT
Socio-economic
6
Composite
SUM DWEN (or DWEA)
Retail units total
RETT
Socio-economic
6
Composite
SUM RETN (or RETA)
Number of parking spaces per dwelling
PRKD
Socio-economic
1
Composite
PRKN/DWEN
Slope
S
Bioclimatic
2,3
Geometry
degrees
Global accessibility rank
ACCG
Mobility
4,6
Network
Closeness
Local accessibility rank
ACCL
Mobility
6
Network
Global movement flow rank
MOVG
Mobility
4,6
Network
Closeness Betweenness
Local movement flow rank
MOVL
Mobility
6
Network
Betweenness
Dwellings proximity
DWEP
Socio-economic
7
Composite
SUM DWEN (or DWEA)
Pedestrian surface share
PEDR
Socio-economic
1
Composite
?
Retail units proximity
RETP
Socio-economic
7
Composite
SUM RETN (or RETA)
Shaded area
SHDA
Bioclimatic
2
Composite
m2
Exposure to prevailing winds
WNDE
Bioclimatic
2,3
Composite
m2
Viewshed area
VWA
General
3
Isovist
m2
Viewshed compactness
VWC
General
3
Isovist
L/A
Number of parking spaces
PRKN
Mobility
1
Survey/Plan
integer
Surface quality
SURF
Bioclimatic
2
Survey/Plan
Attribute
Vegetation type
VEG
Bioclimatic
2
Survey/Plan
%share
13. Attributes applicable to urban formulation (Gil et al 2009)
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Annex 4 The diagram shows the main classes of pre-design phase. The core ontology (Blocks, Focal Points,
Networks, and Zones) is located in the purple boxes of the diagram entities. Its shared superclass is Design Core (light purple and dark green boxes).
34. Syntax class hierarchical tree (above left), exported piece of XML Schema (above centre), CPL diagram classes, subclass-superclass hierarchy, and slots (middle right), CPL diagram zoom - the design core Networks, Zones, Blocks, and Landmarks (at the bottom).
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