Information Formalization by _AKADA_

INFORMATION FORMALIZATION

ABSTRACT

=[ This thesis explores the connection between information representation and architectural expression. Beginning with the premise that architecture should develop through a process based on the analysis of pertinent information, it investigates different representation techniques. Specifically, the use of complex data modelling and visualization theories are investigated, in order to provide better insight into the networked problems that the architectural project will address. The subsequent process of architecturalization of this data model will be contrasted with the process of architecturalization that proceeds from diagram based analysis techniques. Both practical and theoretical topics will be addressed, in order to provide a solid framework for continuing investigation on the incorporation of big-data into architecture. ]

#A Thesis Presented To The Undergraduate Faculty Of

THE NEWSCHOOL OF ARCHITECTURE & DESIGN

#In Partial Fulfillment Of The Requirements For The Degree #Of

BACHELOR OF ARCHITECTURE

#by

ANDREW KENNETH ANDERSON

June 2018 San Diego, CA

VII

INFORMATION FORMALIZATION

#A Thesis Presented To The Undergraduate Faculty Of

THE NEWSCHOOL OF ARCHITECTURE & DESIGN

#by

ANDREW KENNETH ANDERSON

Approved by:

Michael Stepner Date =

Eric Farr, PhD Date =

Undergraduate Chair

Thesis Supervisor

VIII

DEDICATION = [

#This thesis is dedicated to... Alexandra Novikov; For her extensive support of every type, without which none of this would be possible. Lisa Jones, Ken Anderson, Mark Jones, Heather Anderson, Masha Spichkin, Richard & Carolee Jones, and Timothy Menezes for their support and encouragement. Roxanna Menezes whom I wish could see this book. My siblings; Rachelle and Geoff Goolsby, Trenton Jones, Emma Anderson, Mackena Jones, Riley Anderson, Caelyn Anderson, and Zach Novikov who have served as inspiration and motivation, and helped to keep me sane. Professors and mentors; who have helped to shape me, especially John Ellis, Matthew Lechowick, John Griffith, Amin Espandiari, and Colum Kucloc. My classmates; who have motivated and challenged me, and continually destabilized my thinking in an important way. ]

Andrew Anderson NewSchool of Architecture + Design Class of 2018

C O N T E N T S Introduction = [ Problem Statement, Critical Position, Thesis Statement, Scope]

Chapter 1 = [ Information in Architecture, Theoretical Issues]

Chapter 2 = [ Diagrams, Summary of Study, Diagram Taxonomy, Site Selection, On-site Building Analysis]

Chapter 3 = [ Data Visualization, Accessing Data, Organizing Data, Modelling Data, Analyzing Data]

Conclusion = [ Architecturalizations, Comparisons, Analysis of Processes, Biases, Implications, Next Steps]

166

Appendices = { A1 ; References A2; Image References}

176

INTRODUCTION

PROBLEM STATEMENT Current architectural expression is often informed by abstracted diagrammatic representations of the determining conditions of a given project (Schumacher, 2010). This process pulls individual factors out of their context, in order to understand and address them, resulting in solutions which are, at best, layered composites of a series of partial solutions. The theory of wicked problems, however, proposes that most problems are composed of a network of interrelated factors which must be considered in an interrelated manner, if an effective solution is to be found (Skaburkis, 2008). Outside of the architectural field, industries like finance, medicine, engineering, and climatology are turning to big-data, in order to inform their decision making with complex understandings of their particular determinants (Sherman, 2014). Much investigation is being done on how to effectively represent this information in comprehensive visualizations in the form of interactive data models. This new form of information representation allows for the simultaneous investigation of the multitude of factors that impact a given design, as well as the relationship between those factors, however, exploration of the spatial and formal implications of its usage in architecture has remained limited. Through an analog process to that which allows current architects to expand their formal and spatial vocabulary through the use of diagrammatic “abstract machines” (Berkel and Bos, 1999), formal and spatial conditions of a novel, complex nature should arise from the use of this new method of data representation as the basis of the design process.

CRITICAL POSITION In the introduction to the book “The Diagrams of Architecture,” Garcia presents a contextual basis for the understanding of diagrams: relating their historical and theoretical bases with their functions. He states that diagrams, in their more current and impactful form, are based, mainly, upon the theoretical definitions related by Deleuze. Deleuze, in turn, based these definitions on the work of Francis Bacon, Marcel Proust, and Michel Foucalt. Deleuze describes the diagram as an “icon of relationships, which specifies… the relations between unformed/unorganized matter and unformalised/unfinalised functions.” Garcia then goes on to elaborate upon Vidler’s definition of the diagram as a multifaceted

instrument, one which functions alternately to “illustrate a definition, aid in the proof of a proposition, or represent the course of results of any action or process.” The difference between drawings and diagrams is that the latter “represents abstractions symbolically” (Garcia, 2010). Garcia goes on to explain that diagrams are used in architecture to fulfill a variety of representational functions: “descriptive, explanatory, normative, interpretive, prescriptive, projective, and predictive” (Garcia, 2010). Indeed, diagrams are used throughout the design process - to begin to understand the determining conditions of a given design project, to project functions and behaviors spatially, to understand the implications of decisions, and eventually to communicate the rationale of decisions to others. While the communication of information to others is an effective use for diagrams, there are major problems associated with their use in processing information to be used as “‘influences’ to be taken into account while preparing a ‘solution’ to the varied problems they propose” (Vidler, 2010). Nevertheless, much architectural investigation since at least the 1980’s has focused around the use of diagrams, as the basis for design methods intended to generate novel spatial and formal systems (Schumacher, 2010). Indeed, UNStudio has claimed that “the function of the diagram is to delay typology and advance design (Berkel and Bos, 1999),” intimating that diagrams should be used during the analysis and design phases of a project, and will allow for novel design solutions. One of the major issues with the use of diagrammatic information representation in the analysis and generation of architecture is that diagrams, by their nature, require a reductionist approach (Shane, 2013). The theories of networks, complexity and chaos, and wicked problems propose that most issues are made up of interrelated causal actors, whose structural relationships inform their manifestations at least as much as do their individual qualities, and effective solutions can seldom be implemented if they address only some issues. As such, the abstraction and simplification of information in the search for architectural concept is problematic. The shift towards the development of “digital topographies,” which relate information that would typically be diagrammed as single elements into a continuous field (Vidler, 2010), illustrates the fact that architects acknowledge this issue, and are working to address it. The field that may provide a solution to this issue is data science, through the use of big-data. This buzz-phrase is used to describe large amounts of diverse data, which is

being generated, collected, and accessed at an exponentially growing rate (Valerdi, 2017). As most industries are beginning to turn to this information for insight (Deutsch, 2015) , there is work being done to find visualization techniques which allow a more comprehensive and exploratory model of information comprehension, that is still accessible to the human mind (Fuchs and Hauser, 2009). These new theories of representation allow visualizations to communicate the complexity that is needed to address issues, and relate complex systems of determinants in an intelligible manner. The complex, interrelated nature of these data models will provide the architectural field with a system of representation that is more closely related to its membersâ&#x20AC;&#x2122; function as the agents in charge of relating disparate systems into coherent and affective compositions. Additionally, as it is apparent that architectural expression is directly related to methods of representation (Olsberg, 2013), it follows that this new method will result in novel formal and spatial manifestations. This thesis proposes research in a series of areas, which, when synthesized, holds the opportunity for an expansion of formal and spatial vocabularies of architecture. The first area of investigation is into the theory of representation of information which relates to diagrams, and the subsequent connection of these theories to architectural expression. Deleuzeâ&#x20AC;&#x2122;s theories, as well as the texts and works of architects who engaged these theories will serve as studies in this area. The second area of investigation is the value of complexity, and the related value of big data, in understanding information. The third area of investigation is into current theories of data visualization, especially of large sets of data. The analysis and relation of these theoretical foundations will inform the experimental manifestation of architecture which will make up the thesis design.

The purpose of this thesis is to develop an understanding of the practical methods, theoretic foundations, and architectural implications of developments in the field of information representation. Therefore, the scope of work for this thesis includes research on a variety of topics, a study on the connection between the typical information representation techniques and architecture, the development of a prototype method and outcome using high-dimensional data in design, and a comparison of that process with an analogous process. The research essays included provide the necessary framework within which this thesis operates. These essays cover the topics of: -Information in Architecture -The Theoretical Basis of the Thesis -Diagrams in Architecture -Data Visualization The essays are accompanied by the aforementioned studies, and the analyses of the process and outcomes of those studies. While the studies undertaken within design fields are not typically scientific, due to inherent subjectivity and the use of intuition in most design work, the studies undertaken here aim to be relatively rigorous. The biases, subjective interpretations, and intuitive steps taken are made explicit, and documentation for the more rigorous work is provided. The conclusion of this thesis will attempt to look towards the possible implications of this work on the future of architecture, and suggest further areas for research or uses in practice.

C H A P T E R

INFORMATION IN ARCHITECTURE + THEORETICAL BASIS

1. The overtly functionalist perspective of architectural design presented here is not intended as a critique of more intuitive and experientially oriented methodologies, nor to devalue the value of architectural systems as providing only systems coherence. Indeed qualities of architectural systems can, and should, exceed mere unification. However, to be able to transcend the plane of functionality, it must be engaged effectively.

INFORMATION IN ARCHITECTURE Architectures are inherently information based. The expression of information in building originally flowed from the logics of construction, with a given element necessarily sized and organized so as to best perform their functions. The modern conception of architecture, as conceived by Alberti, focuses not on the actual building process, but on the imagination and representation of that building information, with any interaction with the physical implications of that design work left outside of the hands of the architect (Payne, 2009). This serves to illustrate the importance of explicit information in the modern field of architecture, as the disconnect from the physical production of a building demands that, even on the basic level of construction logics, information must be dealt with in a codified manner, with at least one degree of distance from the physical systems. As the role of the architect has become more separated from the physical act of building which, in turn, has become more complex, information has become even more central to architecture. The increasing complexity of building has been mirrored by an increase in the general complexity of human systems, and our increasing understanding of the complexity of the relationships between those systems in which architecture plays a role has further contributed to informationâ&#x20AC;&#x2122;s essential role in the field. Indeed, information may be the defining trait of architecture today, the trait that separates it from the arts, and the foundation of much of the progress that has been made in the field since its inception. One of the major roles of the architect today is the orchestration of various agents in the design and construction of a building, in order to insure that the product performs as a functional and aesthetic composition. A role that is vastly different from the â&#x20AC;&#x153;master builderâ&#x20AC;? model of the architect (Garber, 2009). The various actors involved each has their own field of knowledge, each of which concerns a system of information which needs to be addressed in a given design. These systems include, but are not limited to, legal, financial, structural, mechanical, ecological, and infrastructural, each of which is made up of a series of constituent parts. Architectural information, including social, contextual, material, experiential, aesthetic, symbolic, and functional, can provide logics which serve to unify these systems into one of relatively greater coherence1. The trend towards integrating the various fields which are engaged during the design process earlier and more fully, is a potent demonstration of the fact that architects have come to understand the importance of that information in delivering a

project. This trend is well described by the members of the Specialist Modelling group at Foster + Partners, who describe a fragmented and specialized group of project contributors each with a specific and limited field of knowledge, who are becoming more integrated and aligned due to pressure to perform within an ecological imperative (Whitehead, Gallou, Thapar, Betti & Craig, 2011). That ecological imperative is the (semi-)global push towards sustainable, or ecologically performative, architecture2 and is another of the major factors demanding informed architecture. The field of architecture has had to come to terms with the fact that its role as the primary actor in reshaping ‘natural’ environments into man-made ones is in opposition with current ideas about the importance of biodiversity and natural conservation. Simultaneously, it is becoming clear that many of the typical building practices, materials, and systems used by previous generations, when combined with the scale of architectural projects, create massive quantities of waste in both material, and resource terms. Many factors including, population growth, relative resource scarcity, and climate change have spurred the architectural field to re-evaluate those typical practices in an effort to alleviate some of its impact on greater systems (Kibert, 2005). This change has served to increase the complexity of many building projects, thereby increasing the relevance of a wider array of information, while also placing greater importance on the performance of a building in relation to systems of information which had previously been engaged. Indeed, Many of the major systems mentioned previously impact the energy use of a building, and understanding the general scientific principles, as well as the specific conditions which will play a role in determining a project’s performance is essential. The ability to collect and access large amounts of data, as well as to perform detailed simulations has contributed to the further understanding that information is essential to designers’ capacity to manage the outcome of a project (Khan & Marsh, 2011). Widespread engagement with groups like the USGBC, as well as the legal codification of performative imperatives, illustrates the pervasiveness of the acceptance of these concepts is in the architectural field. Similarly, the variety and quantity of research being done to develop new methods, materials, products, and concepts which enhance the performance of a given building product shows how important the field has deemed information to its pursuit of ‘sustainable’ architecture (Garber, 2009) (Hensel, 2013) (Peters, 2011).

2. Sustainable, green, or performance based architecture should be understood here not as a stylistic representation of ecological principles in architectural logics, but rather as a performative function of all buildings; an understanding that the costs of a building include all resource use, rather than strictly monetary resources.

3. More on theories of information, information technology, information philosophy, and information culture will be discussed later.

Of course, the sustainability movement is not the first example of performative architecture, nor do its goals encompass the range of functions that a building must perform. Hensel places the origins of the concept of performance in architecture in the 1860â&#x20AC;&#x2122;s, although, depending on oneâ&#x20AC;&#x2122;s definition of performance, the date could be much earlier. He then describes a variety of chronologically successive, and theoretically oriented performance definitions divided into five groups. Each of the first four types describes a different goal which the performative architectures of a given era or movement would seek to attain, namely: symbolism and meaning, formal, functional, and events. The fifth (his apparent preference) is made up of some combination of the first four aspects, and the relationships between these (Hensel, 2013). These categories demonstrate the diversity of systems of logic which can be used to drive a given design philosophy and to select criteria for determining the success of a project. Each demands a specific set of theories, and engages different systems of determining elements which will influence the outcome of a design problem. Again, information is key, and the breadth of the necessary information is noteworthy. Finally, information has become central to culture throughout much of the world (Briggle & Mitcham, 2009)3, and as such its importance, and the perceptions of its importance have vastly increased. As Deutsch relates in his book, Data Driven Design, clients are demanding increasing transparency in the process and expected outcomes of design projects (Deutsch, 2015). The practical implication of this development is that quality information is now more important than ever before, across the full spectrum of systems. Additionally, the documentation and presentation of that data is also becoming a major priority, both within and outside of the architectural field. The production of information during the design process is further intensified by Building Information Modelling, and the potential for those models to be turned into fabrication information for digital manufacturing processes. Architecture firms are also beginning to examine the information they generate internally, in order to create efficiency, to aid in marketing, and to test implementations of ideas, amongst other purposes. So, in addition to leveraging existing information, in order to understand and address problems, architecture produces information of varied natures in large quantities, and is being asked to do so more and more.

While the analysis of specific pieces of architecturally relevant information like site conditions has long been considered a central exercise in the design process (White, 2013), the less explicit incorporation of information in architectural design is equally important. Indeed, the connection between architecture and information is essential, and will only become more as information, technology, and human culture continue to evolve together. As such, understanding the way in which information is analyzed and synthesized is essential to the considered progress of the architectural field.

REFERENCES Briggle, A., & Mitcham, C. (2009). From the Philosophy of Information to the Philosophy of Information Culture. Information Society, 25(3), 169-174. doi:10.1080/01972240902848765 Deutsch, R. (2015). Data-Driven Design and Construction . Hoboken: Wiley. Garber, R. (2009). Closing the gap (p. 9). Chichester: Wiley. Hensel, M. (2013). Performance-Oriented Architecture. Chichester: Wiley. Khan, Azam & Marsh, Andrew. (2011). Driving an Ecological Agenda with Project-Led Research. In T. Peters, Experimental Green Strategies (pp. 82-88). West Sussex: John Wiley & Sons Ltd. Kibert, C. (2005). Sustainable construction (p. 1-55). Hoboken: Wiley. Payne, A. (2009). Materiality, Crafting, and Scale in Renaissance Architecture1. Oxford Art Journal, 32(3), 365-386. doi:10.1093/oxartj/kcp035 Peters, T. (2011). Experimental green strategies. Hoboken, N.J.: Wiley. White, E. (2013). Site analysis. [United States]: ArchiBasE Press. Whitehead, H., Gallou, I., Thapar, H., Betti, G., & Craig, S. (2011). Driving an Ecological Agenda with Project-Led Research. In T. Peters, Experimental Green Strategies (pp. 30-32). West Sussex: John Wiley & Sons Ltd.

THEORETICAL BASIS INTRODUCTION

1. The influence of these theories as systems through which information is processed and received can be observed already, as the theories discussed will typically concentrate on relationships and interconnection, informing even the understanding that they can be looked at in tandem.

Recent architectural discourse has often drawn on the work of thinkers working in various fields including philosophy, sociology, the hard sciences, cultural studies and more, as a way of validating concepts within a pre-systematized logical framework. While useful as a wellspring from which to draw concepts that can embolden architectural imagination or as critical tools which can help refine those concepts, these systems will also become the lens through which information is perceived and understood. If information can be seen as central to architectural pursuits, it follows that the specific methods, systems, or perspectives with which that information is understood will have a major impact on the architectural project. So, comparing and contrasting some of the major theoretical systems which have been investigated in recent architectural discourse should provide some insight into the main trends in how the architectural field interprets information and locates itself in relation to that information. This thesis posits that abstraction, as a tool for understanding, is problematic, and the theories discussed here demonstrate why problems, including design problems, have a nature which precludes them from being addressed using abstraction methods. Instead, the frameworks related in this section demonstrate the superiority of complex, relational, systems thinking in problem solving, and the fact that contextualizing information is essential for accurate analysis.

INFORMATION The theoretical basis for the argument which will be presented here lies in a series of interconnected1 ideas. The central concepts of these systems of thought contain many similarities, although they are defined by certain unshared traits as demanded by identity. The theories presented have been examined in recent architectural discourse, but do not cover the extent of that discourse, as this thesis does proceed from a specific theoretical framework rather than attempting to address all logical systems. The foundational theory for this thesis is that of wicked problems, and is further enhanced with complexity, dynamic network, and actor-network theories. When examined in conjunction, these related theories provide at least one major imperative, amongst the larger perspectival system they engender. This imperative is the demand for contextualization and avoidance

of abstraction. While these theories tend towards highly interconnected, possibly even unified, ontologies which have been disputed, it should be noted that even systems that criticize some of their aspects typically do have a strong focus on the relationality. This fact likely implies that there is a larger tendency towards understanding things as parts of larger systems, regardless of the discreteness or unification of the underlying ontological system, further supporting contextualization in its opposition to abstraction. Finally, the emphasis on relationships, and the qualities of those relationships in each of these theories means that even if it is possible to understand the individual elements with some degree of abstraction, the effects generated by the systems will be impossible to understand or predict. This is due to the fact that the relationships between elements make up the structure of a system, and that structure, along with the way information flows through it likely has more impact than the elements themselves. The theory of wicked problems, as delimited by Rittel and Webber in various papers including Dilemmas in a General Theory of Planning (1973), describes a set of design problem “which are ill-formulated, where the information is confusing, where there are many decision makers and clients with conflicting values, and where the ramifications in the whole system are confusing” (Churchman, 1967). Rittel and Webber specify specific characteristics of these problems in the 1973 work in ten parts: “ 1.There is no definitive formulation of a wicked problem. 2.Wicked problems have no stopping rule. 3.Solutions to wicked problems are not true/false, but good bad. 4.There is no immediate or ultimate test of a solution to a wicked problem. 5.Every solution to a wicked problem is a “one-shot operation.” 6.Wicked problems do not have an enumerable (or exhaustively describable) set of potential solutions, nor is there a well-described set of permissible operations that may be incorporated into the plan. 7.Every wicked problem is essentially unique. 8.Every wicked problem can be considered a symptom of another wicked problem.

2. Characteristic 8: every wicked problem is a symptom of another wicked problem. 3. Characteristics 1,9: these show that depending upon the perspective of the designer, or the expected solution, any given number of factors could be a cause. This implies a large number of potentially contributing factors. Characteristic 6: if each solution implies its own locus of intervention, those individual factors must also be unenumerable.

9.The existence of discrepancy representing a wicked problem can be explained in numerous ways. The choice of explanation determines the nature of the problem’s solution. 10.The designer has no right to be wrong. “ -(McCall and Burge, 2018)

4. Ignoring the more paralytically pessimistic potentials of the concept of wicked problems, as must be done if any design or planning operation is to be undertaken, but rather using the issues associated with wicked problems as a set of issues to be addressed to the fullest extent possible.

This elaboration of the characteristics of wicked problems, despite some receiving critical attention, seems to provide a good description of many of the problems engaged by architects and urban planners, as well as in politics, society, and systems like the climate. While certain parts of the description continue to provide powerful tools with which to address issues, some of these characteristics are thought to have been addressed through technology or other changes in design processes (Zellner & Campbell, 2015, p. 458). More importantly, the theory of wicked problems implies that every planning or design problem can be considered to be interrelated2, and that a large number of ill-defined factors must be addressed in order for any solution to be viable (if they can at all)3. Further, the theory of wicked problems has been related to complex systems theory and actor-network theory, which demonstrates that it is, at some level, based on a sort of ecological systems based thinking. Lastly, the investigation of the connection between wicked problems and those newer approaches has possibly provided tools to alleviate some of the issues associated with wicked problems. In the paper “Changing the Tobacco Use Management System: Blending Systems Thinking with Actor-Network Theory,” Young, Borland, and Coghill discuss wicked problems as a kind of contextualization of the problem they are attempting to address, specifically tobacco use. They attempt to address the wicked problem4 by first implementing a systems thinking approach, wherein one attempts to identify a given system’s contributing sets of subsystems, which are in turn made up of relationships and further subsystems, in as much detail as possible. Additionally, the environment must be described, including elements which might be outside the specific system, but are nonetheless impacting the system in some way(p.254). Their use of Actor-Network theory is an attempt to destabilize that system by providing a framework for dealing with the varied nature of system elements, and also for extra-systemic relationships to be understood and incorporated into the model(p. 259). Indeed, the authors believe that the added dimensions of “heteroge-

neous mechanics” and “trans-disciplinary, trans-system, and trans-subsystem learning” does allow for the addressing at least some of the issues in a wicked problem, if not the problem as a whole (Young, Borland & Coghill, 2012, p.276). The use of Actor-Network theory as a system of logics informing the understanding of academics and decision makers has been increasing in recent years, perhaps because of its perceived ability to address systems in a more comprehensive or effective manner than static systems methodologies. One major reason for this is the emphasis on relational qualities, the methods that an actor uses. Latour critique sociology as describing elements as manifestations of a given social system, while Actor-Network theory would describe how these elements may, or may not, be linked in such a way as to produce a social system (2008, p.8). He goes on to describe how it is more important to understand the dynamic way that a society is constantly reformulating itself through the trans(re)lations of the actors which are part of it, than it is to understand how a stable society is shaping its members. Actor-Network theory has been shown to inform powerfully effective tools for engaging complex heterogeneous systems(Young, Borland & Coghill, 2012, p.276), and its expanded use in planning and design (Farias, 2010) shows that there is a trend towards perceiving issues as those kind of systems. Further, the apparently effective application of its principles means that it does effectively describe and subsequently predict the factors which make up those issues. Complex systems theory has also been shown to contain a raft of principles which address some of the issues which make wicked problems so wicked(Zellner & Campbell, 2015). Complex systems are, like those in Actor-Network assemblages, composed of heterogeneous parts that interact with each other in specific ways. These parts and interactions “give rise to a coherent organization with its own attributes, behaviours and trajectory(p. 459).” Analysing the collective behaviors of all the single elements in a system will not predict its behavior, but rather the interactions, or relationships between them, must be considered. Additionally, the manner in which (causal) information flows through a given system gives rise to some of the more interesting phenomenon which complexity theory can effectively engage: Feedback, Emergence, non-linearity, adaptation, etc. This model is another ecological systems based approach, with an emphasis on relationality, and widespread use in the effective modeling of real world issues.

A final ontological perspective, one which has recently entered architectural discourse and generated some controversy, is Object Oriented Ontology. Contrary to the aforementioned relationally based theories, OOO considers things as discrete objects, or perhaps hyper-discrete objects. Harman defines his theory in contrast to relational theories in his response to Schumacher’s “A Critique of Object-Oriented Architecture,” (Harman, 2018) however, while the ontological objects exist in a non-relational realm and contain qualities that can never be accessed by relation, what subjective, interactive, accessible realm there is is determined by the specific qualities which are engaged by specific other objects in their interactions. For instance, Morton explains withdrawal through the example of the way a table is exhibiting different characteristics to a fly, the floor, him, a coffee cup, the ceiling, a wall, etc. (Morton, 2018), meaning to explain that no two objects will ever discover the completeness of one another. However, this description also implies that the specific relationship between any two objects actually means a lot, as it determines, at a minimum, the shape of sensual objects and sensual qualities, and generates new (larger) objects. Inasmuch as a “real object arises from a descending chain of countless smaller components (Harman, 2011, p.122),” the relationships between each of these different objects appear very significant, even in this philosophy of discreteness. The prominence of relationality in these various, relevant, and popular frameworks for thought demonstrates its importance in understanding and working with information. Technological advances have made it possible to model and investigate these more complex relational systems, and to work with the results in a way that would have been impossible before. The power of these systems can be seen in fields like medicine, meteorology, and ecology, where large amounts of heterogeneous information is collected, and the systems behave in complex (but relatively simple) manners. In contrast, decontextualization, or abstraction, is not widely embraced in current problem solving methodologies, because of its limitation of effective results, and distortion of reality. Indeed, even philosophies of discreteness and abstraction, like OOO, must engage these traits within a larger framework of relationships. As such, context, relationships, qualities, structures, and more should all be considered essential to the understanding of information, while abstraction should be avoided.

REFERENCES Churchman, C. (1967). Wicked Problems. Management Science, 14(4), B141-b142. Farias, I. (2010). Introduction: Decentering the Object of Urban Studies. In I. Farias & T. Bender, Urban Assemblages:How Actor-Network Theory Changes Urban Studies (pp. 2-20). New York: Routledge. Harman, G. (2011). The quadruple object. Winchester: Zero. Harman, G. (2018). Response to Schumacher. In M. Benedikt & K. Bieg, Center 21: The Secret Life of Buildings (21st ed., pp. 90-97). Austin: Center for American Architecture and Design. Latour, B. (2008). Reassembling the social. Oxford: Oxford Univ. Press. McCall, R., & Burge, J. (2018). Untangling Wicked Problems. Retrieved from https://pdfs.semanticscholar.org/c31c/89 4dcf93ef2826790db267070061670f77e1.pdf Morton, T. (2018). OOO Class 1 (Embedded Video and MP3). Retrieved from http://ecologywithoutnature.blogspot. com/2012/04/ooo-class-1-embedded-video-and-mp3.html Young, D., Borland, R., & Coghill, K. (2012). Changing the Tobacco Use Management System: Blending Systems Thinking with Actor-Network Theory. Review Of Policy Research, 29(2), 251-279. doi:10.1111/j.15411338.2011.00550.x Zellner, M., & Campbell, S. D. (2015). Planning for deeprooted problems: What can we learn from aligning complex systems and wicked problems?. Planning Theory & Practice, 16(4), 457-478. doi:10.1080/14649357.2015.10 84360

C H A P T E R

DIAGRAM THEORY + DIAGRAMS TAXONOMY + ON-SITE COMPARISON BUILDING ANALYSIS + SITE SELECTION + PROGRAM ANALYSIS

D I A G R A M S INTRODUCTION The methodologies used to analyze, internalize, and represent information have a major impact on the way that information is understood, and, because information is the perceived and catalogued characteristics of some object, therefore on the information itself. Limitations in technology, combined with con(temporarily) lauded, but currently unfashionable, theoretical orientations have made diagrams the information representation method of choice for architects. Of course, usage of diagrams was in no way unique to architects, and visualization of information in this manner can be seen across the range of human endeavours. With architecture, however, the implications of this are even more pronounced than in other fields, likely because architecture’s outcome is typically spatial in nature, just as the diagram is a spatialization of information. Deleuze and Guattari claim that a diagram, “constructs a real that is yet to come, a new type of reality (2009, p.142),” a prospect which is directly aligned to the architects’ self-concepted role. Indeed, the potentialities for the formalization of diagrams has been accepted and pursued in architecture since at least 1980’s (Schumacher, 2010), although earlier examples exist including the works of some Bauhaus members in the 1930’s which herdeg sees as “decorated diagrams (1985),” Bentham’s panopticon design of the late 18th century which is seen as a direct translation of a social diagram, and perhaps even early religious achitectures, whose expression was often traced over proportioning systems derived from mathematic geometric abstractions. The recent use of diagrams to inform architectural product, however, has become increasingly explicit. This increase may be related to an increase in the number and variety of perceived performative indicators of architectural projects, or to a desire to incorporate ideas and determinants from outside the architectural sphere into a given design, both of which demand that more information be analyzed and incorporated into the project. Perhaps the potentials implied by Deleuze and Guattari’s “abstract machine(1987, p.142)” conception of diagrams has lead to this trend, or perhaps it is simply a byproduct of the way in which representation tends to impact architectural outcomes (Olsberg, 2013). Regardless of the reason for, or critical objections to, this

approach, the diagram to architecture process is one which is regularly demonstrated throughout the architectural field today. It has been shown that architecture is inherently information driven and that the variety and complexity of information which is being related to architecture is growing as the relationality of systems with which architecture engages has been acknowledged. A diagram’s natural demand for abstraction (Shane, 2013) means that their use as information representations is inadequate to address those systems. Nevertheless, understanding the theory that underpins architectural diagramming, as well as the implementation of that theory in the design process is necessary, if the process by which information is formalized is to be discovered1.

ON THE USE OF DIAGRAMS TO PROCESS ARCHITECTURAL INFORMATION Architecture has used diagrams to draw exteriorities into its expression, possibly since the inception of the idea of architecture, however it has been the last 60, or so, years in which the focus of architectural knowledge has shifted from drawing to diagramming (Somol, 1999, p. 7). The result of this shift is “the diagrammatic practice (flowing around obstacles yet resisting nothing)” and a model of the architect in which “he or she becomes an organizer and channeler of information” as the forces (in addition to gravity) which are considered in a project have expanded2 (Somol, 1999, P.24). So, the impetus and ultimate goal for diagram based architectures might be the internalization and formalization of externalities, the analysis and processing of information, in order to turn it into architectural information. Indeed, this does seem to be the purpose behind Van Berkel’s use of diagrams in order to “delay typological fixation, (Van Berkel & Bos, 2010, p. 224), OMA’s hypothesis that “any piece of information can potentially generate an architectural theme or concept (Deen and Garritzmann, 2010, p.228), and Reiser + Umemoto’s search for patterns in matter interpreted through the structure of the diagram (Reiser & Umemoto, 2010, p.250). Each of these examples cite the use of diagrams as a tool for the incorporation of outside information into the architectural design process, albeit in vastly different manners. Another, more explicit example of this is White’s Site Analysis which documents standard diagrams for analysing each factor, or determinant which the contextual nature of

1. Diagram history and architectural connections has been briefly addressed in the introduction to this book, and within the comprehensive book The Diagrams of Architecture, edited by Garcia. This chapter will attempt to more deeply analyze the types of information which have been used to inform architectural manifestations, as well as the abstract nature of diagrams, and the way diagrams have been used in architecture. 2. As has been related previously.

a given site might provide. Whiteâ&#x20AC;&#x2122;s argument for the need for this information is not majorly dissimilar to the one presented here, and given todayâ&#x20AC;&#x2122;s technologies, he may have proposed a similar methodology to that which is proposed in this thesis. Throughout the book, he demands the architect understand vast systems of information and attempt to relate all of those systems together. Unfortunately, his most powerful tool, the transparent overlay, would never allow a full understanding of those systems, as he elaborates eight categories of site related, architecturally relevant informations, each with tens to hundreds of sub-elements, each of which should be analysed (White, 1983). The diagram is used to spatialize this information, in an effort to see how a given building might react to them, in addition to providing a mapping of strictly informational nature. If you add to these the cultural, social, symbolic, economic, structural, material, mechanical, etc. systems which are both intrinsic and extrinsic to architecture but have been at some times used to inform it, the sheer quantity of influencing factors makes the use of diagrams for the interpretation of information, in a way that maintains the relational qualities of those systems impossible.

ON THE ARCHITECTURALIZATION OF DIAGRAMS Not only have recent years seen an increase in the use and significance of diagrams in the processing of architectural information, but they have also seen a concurrent increase in the impact of those diagrams on architectural form and space. At times diagrams have been used to map forces with which spaces and forms have been pushed or pulled, as systems over which architectural form has been traced, as conceptual organizational systems, or as representations to be translated directly into architectural forms. The different methods, elements, types, and projection systems are used together in a myriad of ways, each of which has different implicated outcomes in the architectural product, and each process uses diagrams in different ways. Nevertheless, it is clear that there is often a direct connection between diagrams and their subsequent architectures, with some of the more interesting examples mining their diagrams for novel formal and spatial relationships. At times the architecture itself has been implicated as a diagram with â&#x20AC;&#x153;Form [acting as]

an instigator of performances and responses, a frame that suggests rather than fixes, that maps or diagrams possibilities… (Allen, 1999 ,p.4).” The most common form of diagram impacted architectures are those which use it to discover some small combination of impacting factors, which are then reacted to in an intuitive manner. These architectures can be seen throughout the field and are not particularly illuminative aside from revealing the opposition between informed and intuitive decision making. A second type, which has more historical applications, is that of the proportional system, or the logical system which is then traced in its architecturalization. These methodologies have been shown to take place in Gothic architecture, where symbolic diagrammatic geometry informs both formal scale, and expressive scale architectural manifestation (Ramzy, 2015). This type of systemization of architecture allows for information to be incorporated into the architecture in a way which may not even be understood by the designer, but that information is typically geometric in nature, and not necessarily extrinsic to the architectural field. Potentials for these kinds of ordering systems are strong, but also carry with them implications related to symbolic aspects, which have been critiqued. The explicit formalization of diagrams can also often be seen in recent architectural works. Kazuyo Sejima may have been the first to have her architecture explicitly called “diagram architecture” in reference to the fact that she uses diagrammatic plans to inform the buildings, however, as Pai notes, plans, sections, and elevations are already diagrammatic in nature (Pai, 2010, p.76). As such, it should not be surprising that architects have begun to read their diagrams, or perhaps draw their diagrams, in a manner which will allow them to extract form from those forms they discover in the representation. The final type of architecturalization is that exemplified by UNStudio, Reizer + Umemoto, and ZHA, amongst other firms. These firms have begun using complex systems of data or diagrams, which sometimes operate more like the data models this thesis proposes, to inform complex and novel spatial and formal conditions. Each of these firms uses different techniques for the visualization and translation of that information, but the usage of it is similar in that the

complex spaces and forms of the visualization of data that is not always spatial in nature, provides spatial and formal opportunities which the designer may not have imagined independently. In this type, the method of visualization chosen can have a major impact on the architecture, and an architect or firmâ&#x20AC;&#x2122;s signature could be determined by their choice of visualization and those datasets which they analyze.

REFERENCES Allen, S. (1999). Points + lines (1st ed.). New York: Princeton Architectural Press. Berkel, B. and Bos, C. (1999). Move . Amsterdam: UN Studio. Deen, W., & Garritzmann, U. (2010). Diagramming the Contemporary: OMAâ&#x20AC;&#x2122;s Little Helper in the Quest for the New. In M. Garcia, The Diagrams of Architecture (1st ed., pp. 228-235). Chichester: John Wiley & Sons Ltd. Deleuze, G., & Guattari, F. (2009). A thousand plateaus. Berkeley, CA: Venus Pencils. Garcia, M. (2010). The diagrams of architecture . Chichester: Wiley, pp.222-227. Herdeg, K. (1985). The decorated diagram. Cambridge Mass.: The MIT Press. Olsberg, N. (2013). THE EVOLVING ROLE OF THE DRAWING. Architectural Review , 233 (1395), 36-43. Ramzy, N. S. (2015). The Dual Language of Geometry in Gothic Architecture: The Symbolic Message of Euclidean Geometry versus the Visual Dialogue of Fractal Geometry. Peregrinations, 5(2), 135-172. Schumacher, P. (2010). Parametric Diagrams. In: M. Garcia, ed., The Diagrams of Architecture . Shane, D. (2013). Recombinant urbanism . Chichester: Wiley. Somol, R. (1999). Dummy Text, or the Diagrammatic Basis of Contemporary Architecture. In P. Eisenman, Diagram Diaries (1st ed.). New York: Universe Publishing. White, E. (1983). Site analysis. [United States]: Architectural Media Ltd.

D I AG R A M F O R M S SHAPE LINE CURVE V EC TO R FIELD G LY P H S C O LO R

D I AG R A M M E T H O D S

QUA N T I TAT I V E S PAT I A L R E L AT IO N A L D E L A M I N AT I V E LAYERING CONCEPTUAL G E N E R AT I V E PROGRAMMATIC

FORM VS METHOD VS ARCHITECTUR E

D I AG R A M P RO J EC T I O N

PL AN SECTION AXONOMETRIC PERSPECTIVE

D I AG R A M U S E

A N ALYSI S SYNTHESIS REPRESENTATITION

FORM VS METHOD VS PROJECTION

DIAGRAM TAXONOMY The use of diagrams in architecture is profusive, By analyzing the connections between forms, methods, projection and use of diagrams and the formal, spatial, and systems expression of the resulting bulilding, it becomes clear that the representation techniques used in the analysis of information plays a major role in the resultant building. Although many of the diagrams shown are communicative in nature, it is clear that these represent the thought processes of the architects and should represent similar diagrams in earlier design phases. This study is a brief analysis of a series of diagrams and their architectural manifestations, and relates the methods, forms, and projection method with different formal, spatial, organizational, and systems manifestations. Its purpose is to find commonalities in these relationships, in order to discover how information representation, in its current state, impacts architecture. The above graph on the opposing page show relationships between methods and forms, and architecture. While many of the relationships are common, the most common is the relational vector method form combination, which typically results in formal directionality and circulation paths. Another common relationship is the direct translation of diagram shape into building shape. These simple connections are the most typical, however, very interesting generative diagrams are also represented, and show how series of diagrams can be layered, resulting in less explicit connections. The lower graph demonstrates how common the different types of diagram combinations are. Perspective relational vector diagrams are the most common of those studied. Other combinations are also used relatively often, and it is likely that all of the combinations are used throughout the design process. The profusion of vector representations shows that architects are often interested in information that adds directionality to geometry. Additionally, when vectors, glyphs, color, and size are added in combination, a single vector could communicate as many as seven dimensions of data at a time. This shows an interest in higher dimensional data. A major trend found in this study is the explicit translation from diagram to architecture, which may follow from the geometric nature of diagrams, and the similarities between diagram representation and typical architectural representation. While some of these buildings result in complexity, they typically attempt to use singular concepts to drive the design, and occassionally layer information to inform a more complex design.

This design, unlike many of those represented in the taxonomy, does not often directly translate its design diagrams into built form. Rather, its representational methodologies show a clear connection with its architectural qualities, with only a few diagram forms appearing as architectural elements. Additionally, this design demonstrates a negotiation between the diagrammed design information, other design information (like budget), and a more intuitive design process. The intuitive aspects of the translation may, in fact, inform the diagram selection and representation rather than the formal qualities of the diagrams pushing the qualities of the design. Nevertheless, the connection is important, as these diagrams do demonstrate a clear tendency towards abstraction. The top diagram to the right shows the legal limits to be investigated in the design. While this diagram may describe a decent amount of information, much is left out that could and should be included in a representation which investigates even this minimal amount of information. The differening zoning on separate parcels of the site, for instance, could be an important limiting factor or influencer of design decisions. The middle diagram is a representation of goals. This kind of diagram is not directly site mapping, and typically has less architectural implication. In this case, however, the designâ&#x20AC;&#x2122;s tendency towards networked and bridged organizations is clearly demonstrated in even these simple diagrams. The last diagram from this

S I T E D I A G R A M A NA L Y S I S

page is a simple representation of traffic patterns. It does not act as a formal or spatial map, but the specific form of vector used, a line with filleted corners, is often seen throughout the design. The diagrams on this page map transit information in a way which is, in this case, highly problematic. The needs of the building are largely defined by the number of users at a given transit type, at a given time, and much data is available with which to build a powerful model to demonstrate more accurately and granularly, the nature of those needs. This more specific information may have been provided by the projectâ&#x20AC;&#x2122;s owner, but nevertheless these diagrams were included in the design package of the architect, and do seem to have had some impact on the design of the project.

The diagrams on this, and the next page show some of the site information which is typically analyzed in most, if not all, projects. These factors are, from top to bottom: 1 = [a sun path and envelope] 2 = [connector vs. separators] 3 = [sound intensity] 4 = [views] Again it is obvious that each of these diagrams has been pulled from its context, and thus does not communicate fully the information needed. The sun path diagram should show the days on which heating or cooling would be needed, and should address the actual site conditions, rather than a simplified version. The disconnection diagram is interesting, because the disconnections highlighted are actually integral to the project, and the connection of these with the other spaces is essential. The sound diagram itself communicates little viable information. The final, and most interesting diagram is the view diagram, whose representation may be the first to directly translate into the architecture. The interesting thing with this is that, despite being a decent indicator of actual view direction, this diagram has no context or granularity. The layering of it with other diagrams results in a building which is

mainly underground, with a small bridge actually engaging with the diagrammed information. This means that, in the end, the building itself, and the majority of users, never benefit from the incorporation of views, sun angles, etc. into the building. While a strong and seemingly effective design, it seems that this option does not consider the information in its complex context, nor with the granularity required to inform strong decisions which result in a more effective capitalization on the natural and contextual resources of the project.

SITE ANALYSIS The site selection for this thesis began with the analysis of two sites, picked for their architectural importance and notoriety, as well as their proximity to San Diego, where the author is located. The sites are the Emerson College Los Angeles Campus, and the Los Angeles Union Station. The methodology for the selection of site is mainly the availability and relevance of data. Two sites have been selected in Los Angeles which have a variety of data related to them. They each have buildings on-site, which will either be redesigned or incorporated into the project. Additionally, each of the sites either has an existing building which have been diagrammatically informed, or has well developed designs for one. These diagram informed designs will serve as the comparative basis for the results of the thesis. Indeed, the results of the two design processes will be evaluated, one against the other, in order to examine how the proposed, big-data informed, process has changed the outcome. As data availability, and not the contents of that data, are key to this thesisâ&#x20AC;&#x2122; investigation, mapping demonstrates quantity and not quality of the associated datasets. The major deciding factors are the availability of analysis diagrams for the on-site design, and the influence of typological data on the project. In both of these categories, Union Station is the stronger candidate, and will be the investigated site for this thesis.

CRITERIA SITE: SITE DATA AVAILABILITY ENVIRONMENTAL DATA AVAILABILITY CONTEXTUAL DATA AVAILABILITY SITE FACTORS IMPORTANCE ENVIRONMENT FACTOR IMPORTANCE CONTEXT FACTOR IMPORTANCE

BUILDING ON SITE: DIAGRAMS INFLUENCE OF DIAGRAMS NOTORIETY BUILDINGS TO KEEP ON SITE TYPOLOGIC DATA AVAILABILITY TYPOLOGIC DATA IMPORTANCE

UNION STATION - LOS ANGELES

The selected site for this thesis is the union station site in Los Angeles, California. This site is currently an intermodal transit facility for which a design for an addition is underway. The overhaul is meant to rework the station in order to accomodate the addition of high speed rail to the services provided and allow for the expansion of current services to meet the needs of the massive transit system overhauls which are planned for the city. The information demands for this project are complex, as they engage infrastructural systems which are already in place, as well as the typical site conditions which any project must consider. Additionally, the program for this project demands analysis of larger scale systems, in order to be able to predict the needs of future occupants in a city that is changing rapidly. This project also has performative demands because of its public nature. These demands insure that environmental and climatic information are also important to the design. Further, the City of Los Angeles also has a number of programs which are intended to guide development of public projects in order to impact the welfare of the city and its inhabitants. Adding further complexity, the site is home to the historic Union Station building, which is a registered landmark, and must be protected. This building, as well as other well functioning buildings on the site, make the analysis of contextual information important. The city also intends to make this site an iconic landmark in the city, providing a symbolic representation of the cityâ&#x20AC;&#x2122;s identity as a progressive transit oriented destination, as well as functional piece of the system. The siteâ&#x20AC;&#x2122;s proximity to historical landmarks and downtown Los Angeles provide many opportunities for this, and make up additional datasets which become important. Los Angeles has made much of its data available to the public, as have many other major polities, and as such, much of the information needed are available. Additionally, the public nature of the planned project also insures that information about its design is publicly available, to an extent not always demonstrated by architectural projects. This allows for a well informed comparison between the current, diagram informed, on-site design, and the thesis proposal.

DATASETS

The datasets presented here are not an exhaustive representation of the extent of data used in this thesis, but instead served to analyze the siteâ&#x20AC;&#x2122;s available quantity of inormation. As will be described later, derivatives of much of this information are required in order to provide architecturally relevant information. Additionally, much information cannot, or should not, be represented in this manner. A more complete list of the data used in this thesis: 2010 Census Block Groups 2010 Census Data By Block Asthma 18 Businesses Active Clean Streets Index Clean Streets Index Grids 2017 Q1 Community Equity and Health Index Connect High Bike WalkCommunties to Medical Facilities and Grocery Stores Connect High Bike Walk Communties to Job Rich Districts Connect LowIncome Communties to High Quality Transit Connect Low Income Communties to Medical Facilities and Grocery Stores Diabetes 18 Over 20112012 First Last Mile Priority Areas Heart Disease 18 Over 20112012 High Injury Network Journey to Work 2013 5 Year Estimates Less Than High School Degree Low Birth Weight Low Income Nighttime LST Hot Spots Obesity 18 Over 20112012 People of Color Physical Activity 18 Population Over 64 Poulation Under 5 Provide Access to LA River Provide Access to Public Schools Provide Access to Universities Social Vulnerability Overall Stacked Priorities Unemployment Contours/Topography 500Year Flood Plain Fault Trace Disaster Routes Liquefaction Zones

Tsunami Inundation Runup Line Shoreline Change Streets Traffic Trees Bureau of Street Services Trees Recreation and Parks Department Bikeways Existing Building Footprints Easements Freeway Exits Historic Cultural Monuments LA City Zoning LA City Parcels Sewer Easements Existing Buildings Solar Radiation Solar Direction Sky Cover and Clouds Cooling Degree Days Heating Degree Days Temperature Humidity Precipitation Air Pressure Wind Direction Pollution Emitters 801 Track 0316 802 805 Track 0316 804 Track 0316 806 Track 0316 American Transit Planning Package (CTPP) Amtrak Stations Metrolink Stations Metro Bus Lines Metro Rail Lines Stops Community DASH Routes Commuter Express Routes Downtown DASH Routes All Metro Stop Times Amtrak Stop Times Metro Fleet Inventory Dimensions for Vehicles in Fleet Inventory This list is also not exhaustive, but represents the majority of datasets accessed and analyzed in the course of this thesis.

The program analysis presented here is the most successful of a series of brute-force solutions to adjacency values in the program. The following pages contain a series of drawings which document various aspects of the program, visualized as a color gradient behind an adjacency visualization which was integratively solved. Qualitative and quantitative aspects have been chosen to connect to various site qualities which can be derived from the available datasets. This allows for the performative selection of spaces by program.

P R O G R A M The major typology of this building is a transit station. While the original designs for the site involve a master planning effort, this thesis will be limited to the transit sttation and accompanying retail, dining, back of house, concourse, and platform areas. This typology is especially pertinent to my thesis because of its nature as a connective building which contains complex flows of people and materials. The very technical nature of spaces to accomodate vehicles allows for an instance of in depth data analysis and modelling, while the public nature of the project insures that much of the relevant data will be available to the general public (and me, by inclusion). All the aforementioned program needs should be included because the complexity of the program synergises with my thesis, allowing for a more complex model in relation to strictly typological information.

MAINT. STORAGE STO STO TORA RAGE RA GE BOH MAINT. PLATF PLA TFORMS: TF ORMS: SHUTTLE PLATFORMS: MAINTENANCE BOH MAINTENANCE PLATF PLA TFORMS: TF ORMS: CAR PLATFORMS: LOCKER LOCKER OCKERSS BOH LOCKERS PLATF PLA TFORMS: TF ORMS: RIDESHARE RIDESHA RIDESHA SHARE RE PLATFORMS: BAGG BAGG GGAG AGEE AG BOH BAGGAGE PLATF PLA TFORMS: TF ORMS: TAXI TAX TAX AXII PLATFORMS: BREAK BOH BREAK BOH ADMIN PLATF PLA TFORM TF ORM ACCESS ACC ACC CCES ESSS ES PLATFORM SECURITY BOH SECURITY PLATF PLA TFORMS: TF ORMS: SUBWAY SUB PLATFORMS: SECURITY SECURITY INFORMATION INFO IN FORMA FO RMATI RMA TION TI ON PARKING PARKING WAITING WA ITING TICKETING PLATFORMS: PLATF PLA TFORMS: TF ORMS: RAIL RAIL PLATF PLA TFORMS: TF ORMS: LIGHT RAIL PLATFORMS: REST RE STRO ST ROOM RO OMSS OM RESTROOMS BAGG GGAG GG AGEE HANDLING AG BAGGAGE

REST VS REST

PLATF PLA TFORM: TF ORM: HSR HS PLATFORM: ROO ROO OOM M DINING ROOM DINING POS RETAIL RETA RET AIL DISPLAY DISPL DISPL SPLAY AY DINING FO FFOOD OOD PREP RETAIL RETA RET AIL POS DINING STORAGE STORA ST ORAGE GE PLATF PLA TFORMS: TF ORMS: PEDESTRIAN PEDES PEDES ESTRIAN TRIAN PLATFORMS: RETA RET AIL ST SSTORAGE TORA ORAGE GE PLATFORMS: RETAIL PLATF PLA TFORMS: TF ORMS: BUS BUS M O T IO ION PLATF PLA TFORMS: TF ORMS: BIKE BIK PLATFORMS: MOTION

MAINT. STORAGE STO STO TORA RAGE RA GE BOH MAINT. PLATFORMS: PLATF PLA TFORMS: TF ORMS: SHUTTLE MAINTENANCE BOH MAINTENANCE PLATF PLA TFORMS: TF ORMS: CAR PLATFORMS: LOCKER LOCKER OCKERSS BOH LOCKERS PLATFORMS: PLATF PLA TFORMS: TF ORMS: RIDESHARE RIDESHA RIDESHA SHARE RE BOH BAGGAGE BAGG BAGG GGAG AGEE AG PLATFORMS: PLATF PLA TFORMS: TF ORMS: TAXI TAXII TAX BOH BREAK BREAK BOH ADMIN PLATF PLA TFORM TF ORM ACCESS ACC ACC CCES ESSS ES PLATFORM SECURITY BOH SECURITY PLATFORMS: PLATF PLA TFORMS: TF ORMS: SUBWAY SUB SECURITY SECURITY INFORMATION INFO IN FORMA FO RMATI RMA TION TI ON PARKING PARKING WAITING WA ITING TICKETING PLATFORMS: PLATF PLA TFORMS: TF ORMS: RAIL RAIL PLATFORMS: LIGHT RAIL PLATF PLA TFORMS: TF ORMS: REST RE STRO ST ROOM RO OMSS OM RESTROOMS BAGG GGAG GG AGEE HANDLING AG BAGGAGE

PUBLIC PUBLIC

PLATF PLA TFORM: TF ORM: HSR HS PLATFORM: ROO ROO OOM M DINING ROOM DINING POS RETAIL RETA RET AIL DISPLAY DISPL DISPL SPLAY AY DINING FO FFOOD OOD PREP RETAIL RETA RET AIL POS DINING STORAGE STORA ST ORAGE GE PLATFORMS: PLATF PLA TFORMS: TF ORMS: PEDESTRIAN PEDES PEDES ESTRIAN TRIAN RETA RET AIL ST SSTORAGE TORA ORAGE GE PLATFORMS: RETAIL BUS PLATF PLA TFORMS: TF ORMS: B US V S P R I VAT V AT E PLATFORMS: PLATF PLA TFORMS: TF ORMS: BIKE BIK PRIVATE

BOH MAINT. MAINT. STORAGE STO STO TORA RAGE RA GE PLATFORMS: PLATF PLA TFORMS: TF ORMS: SHUTTLE BOH MAINTENANCE MAINTENANCE PLATFORMS: PLATF PLA TFORMS: TF ORMS: CAR BOH LOCKERS LOCKER LOCKER OCKERSS PLATFORMS: PLATF PLA TFORMS: TF ORMS: RIDESHARE RIDESHA RIDESHA SHARE RE BOH BAGGAGE BAGG BAGG GGAG AGEE AG PLATFORMS: PLATF PLA TFORMS: TF ORMS: TAXI TAX TAX AXII BOH BREAK BREAK BOH ADMIN PLATFORM PLATF PLA TFORM TF ORM ACCESS ACC ACC CCES ESSS ES BOH SECURITY SECURITY PLATFORMS: PLATF PLA TFORMS: TF ORMS: SUBWAY SUB SECURITY SE CURITY INFORMATION INFO IN FORMA FO RMATI RMA TION TI ON PARKING PARKING WAITING WA ITING TICKETING PLATFORMS: PLATF PLA TFORMS: TF ORMS: RAIL RAIL PLATFORMS: LIGHT RAIL PLATF PLA TFORMS: TF ORMS: RESTROOMS REST RE STRO ST ROOM RO OMSS OM BAGG GGAG GG AGEE HANDLING AG BAGGAGE PLATFORM: PLATF PLA TFORM: TF ORM: HSR HS DINING ROOM ROO ROO OOM M DINING POS RETA RET AIL DISPL DI SPLAY SPL AY RETAIL DISPLAY DINING FOOD FOOD PREP FO RETAIL RETA RET AIL POS DINING STORAGE STORA ST ORAGE GE PLATFORMS: PLATF PLA TFORMS: TF ORMS: PEDESTRIAN PEDES PEDES ESTRIAN TRIAN RETAIL RETA RET AIL ST SSTORAGE TORA ORAGE GE PLATFORMS: BUS PLATF PLA TFORMS: TF ORMS: B US C O N N EC T I O N TO T O ‘ N AT U R E ’ PLATFORMS: PLATF PLA TFORMS: TF ORMS: BIKE BIK LOW HIGH

MAINT. STORAGE STO STO TORA RAGE RA GE BOH MAINT. PLATF PLA TFORMS: TF ORMS: SHUTTLE PLATFORMS: BOH MAINTENANCE MAINTENANCE PLATF PLA TFORMS: TF ORMS: CAR PLATFORMS: LOCKER LOCKER OCKERSS BOH LOCKERS PLATF PLA TFORMS: TF ORMS: RIDESHARE RIDESHA RIDESHA SHARE RE PLATFORMS: BAGG BAGG GGAG AGEE AG BOH BAGGAGE PLATF PLA TFORMS: TF ORMS: TAXI TAXII TAX PLATFORMS: BREAK BOH BREAK BOH ADMIN PLATFORM PLATF PLA TFORM TF ORM ACCESS ACC ACC CCES ESSS ES SECURITY BOH SECURITY PLATF PLA TFORMS: TF ORMS: SUBWAY SUB PLATFORMS: SECURITY SE CURITY INFORMATION INFO IN FORMA FO RMATI RMA TION TI ON PARKING PARKING WAITING WA ITING TICKETING PLATF PLA TFORMS: TF ORMS: RAIL RAIL PLATFORMS: PLATF PLA TFORMS: TF ORMS: PLATFORMS: LIGHT RAIL REST RE STRO ST ROOM RO OMSS OM RESTROOMS BAGG GGAG GG AGEE HANDLING AG BAGGAGE

LIGHTING HIGH

PLATF PLA TFORM: TF ORM: HSR HS PLATFORM: DINING ROOM ROO ROO OOM M DINING POS RETA RET AIL DISPL DI SPLAY SPL AY RETAIL DISPLAY DINING FOOD FOOD PREP FO RETAIL RETA RET AIL POS DINING STORAGE STORA ST ORAGE GE PLATF PLA TFORMS: TF ORMS: PEDESTRIAN PEDES PEDES ESTRIAN TRIAN PLATFORMS: RETAIL RETA RET AIL ST SSTORAGE TORA ORAGE GE PLATFORMS: PLATF PLA TFORMS: TF ORMS: B US BUS INTENSITY PLATFORMS: PLATF PLA TFORMS: TF ORMS: BIKE BIK LOW

GRAND GRAND

PLATFORM: PLATF PLA TFORM: TF ORM: HSR HS DINING ROOM ROO ROO OOM M DINING POS RETAIL RETA RET AIL DISPLAY DISPL DISPL SPLAY AY DINING FO FFOOD OOD PREP RETAIL RETA RET AIL POS DINING ST SSTORAGE TORA ORAGE GE PLATFORMS: PEDESTRIAN PLATF PLA TFORMS: TF ORMS: PEDES PED ESTRIAN ES TRIAN RETAIL RETA RET AIL STORAGE STORA ST ORAGE GE PLA PLATFORMS: PLATF TFORMS: TF ORMS: B BUS US V S I N T I M AT ATE PLATFORMS: PLATF PLA TFORMS: TF ORMS: BIKE BIK INTIMATE

BOH MAINT. MAINT. STO SSTORAGE TORA TO RAGE RA GE PLATFORMS: PLATF PLA TFORMS: TF ORMS: SHUTTLE BOH MAINTENANCE MAINTENANCE PLATFORMS: PLATF PLA TFORMS: TF ORMS: CAR BOH LOCKER LLOCKERS OCKERSS OCKER PLATFORMS: RIDESHARE PLATF PLA TFORMS: TF ORMS: RIDESHA RIDE SHARE SHA RE BOH BAGGAGE BAGG BAGG GGAG AGEE AG PLATFORMS: PLATF PLA TFORMS: TF ORMS: TAX TTAXI AXII BOH BREAK BREAK BOH ADMIN PLATFORM ACCESS PLATF PLA TFORM TF ORM ACC A CCES CC ESSS ES BOH SECURITY SECURITY PLATFORMS: PLATF PLA TFORMS: TF ORMS: SUBWAY SUB SECURITY SE CURITY INFO IN FORMA FO RMATI RMA TION TI ON INFORMATION PARKING PA RKING WAITING WA ITING TICKETING PLATFORMS: PLATF PLA TFORMS: TF ORMS: RAIL RAIL PLATFORMS: PLATF PLA TFORMS: TF ORMS: LIGHT RAIL REST RE STRO ST ROOM RO OMSS OM RESTROOMS BAGG GGAG GG AGEE HANDLING AG BAGGAGE PLATFORM: PLATF PLA TFORM: TF ORM: HSR HS ROO ROO OOM M DINING ROOM DINING POS RETAIL RETA RET AIL DISPLAY DISPL DISPL SPLAY AY DINING FO FFOOD OOD PREP RETAIL RETA RET AIL POS DINING ST SSTORAGE TORA ORAGE GE PLATFORMS: PEDESTRIAN PLATF PLA TFORMS: TF ORMS: PEDES PED ESTRIAN ES TRIAN RETAIL RETA RET AIL ST SSTORAGE TORA ORAGE GE PLA PLATFORMS: PLATF TFORMS: TF ORMS: B BUS US C O N N EC T E D V S S E PA P A R AT E PLATFORMS: PLATF PLA TFORMS: TF ORMS: BIKE BIK CONNECTED SEPARATE

STORAGE BOH MAINT. MAINT. SSTO TORA TO RAGE RA GE PLATFORMS: PLATF PLA TFORMS: TF ORMS: SHUTTLE BOH MAINTENANCE MAINTENANCE PLATFORMS: PLAT PL ATFFORMS: CAR AT BOH LOCKER LLOCKERS OCKERSS OCKER PLATFORMS: RIDESHARE PLAT PL ATFFORMS: RIDES AT RID ESHA ES HARE HA RE BAGGAGE BOH BAGGA BA GGAGE GGA GE PLATFORMS: PLAT PL ATFO AT FORRMS: TAXI FO TAXI BOH BREAK BOH ADMIN PLATF PLA TFORM TF ORM ACC A CCES CC ESSS ES PLATFORM ACCESS BOH SECURITY SECURITY PLATFORMS: PLAT PL ATFFORMS: SUBWAY AT SUB SECURITY SECURIT SE CURITYY CURIT INFORM INF ORMAT ORM ATIO AT ION IO N INFORMATION PARKING PAR PA RKIN KINGG WAITING WAI WA ITIN TINGG TICKETINGG TICKETIN PLATFORMS: PLATF PLA TFORMS: TF ORMS: RAIL PLATF PLA TFORMS: TF ORMS: LIGHT RAIL PLATFORMS: RESTROOMS REST RE STRO ST ROOM RO OMSS OM BAGGAGE BAGGA GGAGE GGA GE HANDLING PLAT PL ATFFORM: HSR AT PLATFORM: DINING RO ROOM OM DINING POS RETAIL DISPLAY RETAIL DISPLA DI SPLAYY SPLA DINING FO FFOOD OOD PREP RETAIL RET AIL POS DINING INING STO SSTORAGE TORA TO RAGE RA GE PLAT PL ATFFORMS: PED AT PPEDESTRIAN EDES ESTRIA ES TRIAN TRIA PLATFORMS: RETAIL STORAGE RETAIL ST STORA ORAGE ORA GE PL PLATFORMS: PLAT ATFFORMS: BUS AT BUS AIR CHANGE AMOUNT PLATFORMS: PLATF PLA TFORMS: TF ORMS: BIKE LOW HIGH

HOURS OF USE

DATA VISUALIZATION ON THE GENERAL NATURE OF INFORMATION VISUALIZATION

1.Although one could imagine the engagement of other senses, like sound, to add further information to a visualization, and these alternate sense visualizations may be being researched now. 2.And many other fields today 3.Projections are here defined as an elaboration of imagination of the future, as opposed to a representation of an understood or previously experienced condition.

Data visualizations are graphic representations of information that use visual1 expression founded on psychological principles of perception in order to provide humans with a better level of access to that information than could be gleaned from simply looking through a table of numbers. They are “instruments for reasoning about quantitative information (Tufte, 1983, p. 9), tools to “condense and communicate information in a vital and meaningful way (Richardson, 2016),” a medium for the revelation of the narratives numbers would tell, the shared language of people and information. As with any sensory art2, data visualization is a tool for generating interest and engagement, a weapon in the battle for attentive resources of today’s hyper-taskers. As such, data visualization must be graphically interesting, coherent, or in another way engaging, while at the same time clear, understandable, granular, and potent. So the potentials inherent in data visualization are muli-fold, they allow for the communication of information at various scales, with high granularity, and with the relationality needed to address design issues successfully, while demonstrating advanced formal and spatial logics that can function as projections3, and providing advanced concepts in generating experiential interest.

Data visualization is not a new field. Indeed, diagrams, and other graphic representation techniques can be considered forms of data visualization, however, the current direction of the field provides a distinction between these older forms of visualization and the state of the art. This distinction is mainly defined by the quantity and complexity of information that is intended to be represented, and the methodologies for doing so. The shift is predicated on the massive amount of information that is being collected, not just on the societal macro level, but also in focused applications like medical imaging, and physics experiments. The need to represent the large, multi-modal, and inter-related datasets requires new methods that sometimes extend on previous methodologies and at other times embrace oppositional principles to them. For the purposes of this thesis, it is important to remember that those data visualizations that embrace abstraction as one of their significant methodologies are problematic, as the theories which underpin the problem this thesis is intended to address demand understanding of data in its complexity. To this end, a distinction needs to be drawn between those data visualizations which do use abstraction yet may still have been produced with large datasets and current media, and what could be deemed a data model, or a representation of information which allows investigation of n-dimensional1 data and its relationships. Another important aspect of data visualization is the difference between visualization to be processed by human beings, and those models which computers can more effectively make use of. While the methods that allow humans to intuitively process information and find patterns have, to a large extent, continued to orbit around abstraction to varying degrees, those methods that allow computers to process information largely do not necessitate that abstraction. As such, both types of visualizations will be examined, in order to ascertain if one methodology is more effective in the pursuit of a design methodology which effectively engages the interconnected network of information which informs the design. This thesis will engage only those types of visualizations which can communicate the information that is used in the design process. However, for the purpose of this research the breadth of the field will be investigated in order to determine how the methods of visualization differ from those of diagrams. Therefore, three rafts of methods for visualization will be studied: static visualization, interactive visualization, and visualization for computers.

1. N-Dimensional data is a type of data which relates N number of different attributes with a particular data â&#x20AC;&#x2DC;object.â&#x20AC;&#x2122; This is the most common and useful type of data, as it allows for more of the multitude of aspects of a specific object to be considered. Additionally, the dimensionality of a given object is increased through its relation to other objects, through the creation of derivatives, or attributes generated through a given interaction. An example of a derivative would be the average of a series of different datasets, or a set of vectors connecting some given points with some other given points.

STATIC VISUALIZATION

2. Some interesting exceptions to this statement have been pursued by architects who have attempted to map data in three-dimensional static assemblies. These works have effectively represented complex information, and created novel spatial formations.

Static visualizations are the most common of the visualization types, and have become pervasive with the increasing interest in information and data. Examples of this type of visualization include diagrams, infographics, charts, graphs, and maps, although this is by no means an exhaustive set. While they can sometimes represent between three and six dimensions of information, they must typically do so in a two dimensional manner2. These representations do typically demand some amount of abstraction, and use layering of methods to express the dimensions of data which exceed those of their particular medium. They are highly susceptible to cluttering, which can serve to limit the communicative effectiveness of the visualization. These are the visualization methods typically seen in static visualization. Glyphs - Glyphs are symbols, icons, and text that are typically used to represent specific characteristics which are typically nominal or representative. The use of a child playing icon, for example, might represent all of the instances of playgrounds, or Xâ&#x20AC;&#x2122;s and Oâ&#x20AC;&#x2122;s might be used to represent bus stops and rail stops respectively. These elements work to provide distinction that is simple to recognize, and in smaller and more unified datasets work well. Their issue is that it takes time to recognize them, especially when many of them exist in a visualization, and that they quickly lose readability in dense or multi-modal datasets. Multi-Dimensional Glyphs - These glyphs will typically contain characteristics which can be manipulated in order to communicate multi-dimensional data. Color, shape, size, opacity, texture, or glyph elements are some examples of manipulable characteristics. The drawback with these glyphs is that in a static image a large number of them become difficult to process, especially if they contain to many dimensions. Brush based glyphs - Brush based glyphs allow for the expression of directionality and or quantitative data within them. These glyphs are a special case of multi-dimensional glyphs.

Vectors - Vectors are both a type of information, and a special symbol which is used to display that information. While the information type can be represented in a variety of ways, the visualization element called a vector is sometimes also called an arrow. These symbols are made up of a line with the point of an angle at its end, and are used to demonstrate directionality. Scaling of the symbol or part of it, is sometimes used to convey amplitude. Vector Fields - Vector fields are agglomerations of vectors which provide directionality for a series of points. These fields are useful for representing flows or other systems which have a series of different directional qualities distributed throughout. Trajectories - Trajectories are traces of movement in time. As such, these elements are communicative at least three dimensions of information, and typically four. As such, Trajectories are often more effective in interactive and dynamic visualizations. Curves - Curves are typically used to either demarcate boundaries, or link similar objects. They are two dimensional objects which can be defined by, or represent, complex mathematics and so are also used to summarize trends in larger information sets. Lines - Lines are simple curves which are defined by a lack of dynamism (no change in directionality). Streambands - Streambands are curves or surfaces which have been derived by the propagation of a particle through a vector field. Shape - Shapes, like curves are demarcations of boundaries, and are usually used to convey inherently spatial data, rather than abstract or quantitative data types. Surfaces - Surfaces can be used to represent topologies, bounded shapes, flows and more. The allow for possibly rather high dimensional data representation, especially when combined with texture, gradients, etc.

Graphs - Graphs are the elemental data visualization tool, they can be used to relate a number of dimensions of data equal to the number of dimensions in the graph (usually up to 3, although adding color could allow some more dimensions to be understood. Color - Color can be used to create sets, convey the quantitative aspects of mapped objects, etc. The effective use of color is a powerful tool in the representation of smaller multi-dimensional data, as it loses its capacity to represent additional types with one implementation. Gradients - A specific implementation of color, this method allows for the visualization of fuzzy information, information which does not occur in steps or binaries. Shadows - Shadows help to communicate depth in the graphic but do not typically represent information themselves. They may be useful in providing contrast to areas with higher information densities. Layering - Layering is the technique typically used in static visualizations, whereby various elements, representing individual dimensions are combined, with the hopes of creating relationships through spatial adjacency. It should be noted that these kinds of relationships are not explicit and must be recognized by the reader of the visualization. Cutaways - Similar to the section in architecture, cutaways remove some data in order to show characteristics which would be obscured.

INTERACTIVE VISUALIZATION Interactive visualization techniques capitalize on the increase in normal and graphic processing power to deliver representations of large, multi-dimensional datasets which can be explored by the user. The mediums available for interactive data visualization are much more restrictive than static visualization, with large amounts of computing power being a necessity, along with a dynamic display and user input sensors. The benefits of interactive data visualization are the ability to quickly and intuitively search through large datasets, and to filter and examine specifics at will. Interactivity solves many of the issues associated with static representations, by allowing the user to move through spatialization of data, to selectively filter that data, to make connections between data points, and to see data related to a particular point at will. The relationship between architecture and interactive data visualization are interesting although, to some extent, they may be mainly poetic in nature. Indeed, the process of designing an interactive visualization mirrors that of architecture, as organization of both the underlying systems (data models), and expression (graphic representation), are important in the function3 of the model. As the capabilities of the visualization are vastly increased by an interactive aspect, a whole new series of methods are added to those which are typically demonstrated by a static visualization. Most, if not all, of the static visualization methodologies are still useful in interactive visualization, and may even have had their issues alleviated through the ability to scale, change view, selectively filter, and explore the information, all of which are impossible in a static representation. Additional methods and elements which are useful in interactive visualizations include: Changing View - The ability to manipulate the point of view of the visualization allows for dynamic exploration of it, revealing different patterns depending on the position of the observer.

3. In visualization function is also understood in a similar way to that of architecture, and includes the performative, experiential, and systematic. Performance, in this case typically includes information comprehension, ease of understanding (wayfinding), speed of the query, and the ease at which derivative information and patterns can be created or demonstrated. A good experience usually means that the interface is intuitive, the graphics have an interesting visual quality, and engagement is increased through these qualities. The systemic qualities are often hidden in the background, but will aid in the other goals of the visualization.

Transfer function Manipulation - a transfer function is the formula which determines how an entity is displayed according to the data input(Pinto & Freitas, 2008). The ability to dynamically effect this is a powerful tool in interactive visualizations. Seeding point selection - Seeding point selection is the placement of starting points which will be used to generate streamlines. Queries - The examination of specific data points, or derived locations on a generated visualization for further information. Region of interest selection - Selective culling of what to display by an area or set. Focusing and linking - Focusing and linking allow the region of interest to be granularized, display more dimensions of its information, or direct the user to additional information of a different format or visualization.

INTEGRATIVE VISUALIZATION Despite the apparent power of interactive visualizations, there are instances in which a pattern is too complex, or a dataset too large, for them to express or the human mind to comprehend. In these instances, the power of a computer to simultaneously hold and manipulate many pieces of information can be enhanced by human pattern finding logics which are embedded into processes. As such, it is sometimes more important that data and relationships are correctly described to the computer, than that they are visually represented clearly for humans. Using the computerâ&#x20AC;&#x2122;s inherent abilities to their fullest allows for manipulation of the more intuitive aspects of design, in order to optimize qualities in a way that is actually effective4. This type of â&#x20AC;&#x2DC;visualizationâ&#x20AC;&#x2122;, in which design solutions are generated as the output of processes which are based upon the interaction of a more or less comprehensive data model with the goals, philosophy, expertise, and intuition of a designer, through the logical manipulation of that designer, provides an avenue for exploration of datasets which outstrip the capabilities of even the most advanced visualizations. These techniques allow the designer to create a construct which relates data points, and finds relevant derivatives. This construct can be evaluated to create granularized information which can then be used to optimize a design towards any set of goals defined by the user of the model. While it may seem that with these visualization methods the designer is removed from the design process, they actually provide a platform through which a designer can express their intuitive process in a strategic, informed manner. Integrative visualization uses the full dataset stored in a given model including voxel, field, or network models to derive and drive further information representation, pattern finding, and formalization procedures.

4. In the diagram driven model of information exploration, the effectiveness of a given strategy is limited by a lack of granularity in information processing and a lack of relational information due to abstraction. As such, a particular analysis can be run, but the information gleaned from these analyses is limited, and any design decision which is intended to address that analysis is, in effect, only addressing the representation. With computer vision methods, actual granular data is used to test every design decision resulting in moves that address real conditions and whose effectiveness can be transparently verified.

REFERENCES Enescu, I., Vescoukis, V., Iosifescu Enescu, C., MĂźller, F., Panchaud, N., & Hurni, L. (2015). Hypercube-Based Visualization Architecture for Web-Based Environmental Geospatial Information Systems. The Cartographic Journal, 52(2), 137-148. doi: 10.1080/00087041.2015.1119469 Ferdosi, B., & Roerdink, J. (2011). Visualizing High-Dimensional Structures by Dimension Ordering and Filtering using Subspace Analysis. Computer Graphics Forum, 30(3), 1121-1130. doi: 10.1111/j.1467-8659.2011.01961.x Fuchs, R., & Hauser, H. (2009). Visualization of Multi-Variate Scientific Data. Computer Graphics Forum, 28(6), 1670-1690. doi:10.1111/j.1467-8659.2009.01429.x Heine, C., Leitte, H., Hlawitschka, M., Iuricich, F., De Floriani, L., & Scheuermann, G. et al. (2016). A Survey of Topology-based Methods in Visualization. Computer Graphics Forum, 35(3), 643-667. doi: 10.1111/cgf.12933 Lima, M. (2013). Visual complexity. New York: Princeton Architectural Press. Liu, S., Wang, B., Bremer, P., & Pascucci, V. (2014). Distortion-Guided Structure-Driven Interactive Exploration of High-Dimensional Data. Computer Graphics Forum, 33(3), 101-110. doi: 10.1111/cgf.12366 McLoughlin, T., Laramee, R., Peikert, R., Post, F., & Chen, M. (2010). Over Two Decades of Integration-Based, Geometric Flow Visualization. Computer Graphics Forum, 29(6), 1807-1829. doi: 10.1111/j.1467-8659.2010.01650.x Pinto, F., & Freitas, C. (2008). Volume visualization and exploration through flexible transfer function design. Computers & Graphics, 32(5), 540-549. doi: 10.1016/j. cag.2008.08.006 Poco, J., Etemadpour, R., Paulovich, F., Long, T., Rosenthal, P., & Oliveira, M. et al. (2011). A Framework for Exploring Multidimensional Data with 3D Projections. Computer Graphics Forum, 30(3), 1111-1120. doi: 10.1111/j.14678659.2011.01960.x Richardson, A. (2016). Data-Driven Graphic Design. New York: Bloomsbury. Staib, J., Grottel, S., & Gumhold, S. (2016). Enhancing Scatterplots with Multi-Dimensional Focal Blur. Computer Graphics Forum, 35(3), 11-20. doi: 10.1111/cgf.12877

Tufte, E. (1983). The Visual Display of Quantitative Information. Cheshire: Graphics Press. Tufte, E. (2008). Envisioning Information. Cheshire, Conn: Graphics Press. Wang, C., & Tao, J. (2016). Graphs in Scientific Visualization: A Survey. Computer Graphics Forum, 36(1), 263-287. doi: 10.1111/cgf.12800 Ward, M. (2002). A Taxonomy of Glyph Placement Strategies for Multidimensional Data Visualization. Information Visualization, 1(3-4), 194-210. doi: 10.1057/palgrave. ivs.9500025

While some static visualizations can combine elements, techniques, and methods, in order to communicated a wider variety of information, they begin to lose clarity and, subsequently, useability with high dimensional data. It should be noted that this drawing is a dense diagram, yet all the information contained within it has been heavily abstracted in order to make it readable. These drawings can be very stimulating to look at and use, however, the abstraction necessary to produce them makes the product less useful as a data visualization. The process of designing with these visualizations is essentially the same as with diagrams [which can be considered static data visualizations].

STATIC VISUALIZATION

When a more pure [less artistic] data representation methodology is used, and dimensionality decreased, it becomes possible to represent somewhat larger datasets, with less abstraction. However, when the dataset is large enough, as is the case with the information for this thesis, finding patterns and meaning in these visualizations becomes nearly impossible. The main issue is that the limited viewpoints makes a comprehensive understanding of the dataset impossible.

INTERACTIVE VISUALIZATION Drawings in interactive visualization dynamically change and have much more to do with creating a coherent composition than with selecting and framing select instances of data. A strong interactive visualization should allow for the quick restructuring of data, based upon the user’s input, anda strong system for the display of high dimensional data, which is easily understood and visually simple. Various elements and methodologies from static visualizations can be combined in these visualizations, and the user can interface with them directly. The user’s impact on a given drawing creates the demand for coherency in colors, systems, and forms, in order for the visualization to remain effective regardless of a given user’s impact.

INTEGRATED VISUALIZATION Drawing with computer vision is more process based than the previous visualization methods. Selecting representations for datasets is important, but the selection and filtering of information is done only for the userâ&#x20AC;&#x2122;s purpose. Instead of abstraction, derivation is typically used to incorporate multiple sets of data into manageable and relevant sets. This differs from true abstraction because these derivations actually add precise data to the sets, rather than pulling out individual pieces. Likewise, the visuals are directly controlled by the user in real time, allowing dynamic querying. The original data used to model architecturally relevant derivatives is maintained, and is displayed and or accessed as a user needs. The dataset is stored and analyzed by the computer, while a user instructs the computer in processing the information. Capitalizing on the ability of the computer to handle large datasets patterns can be found and related in ways that no human could, of course the process is meant to provide actionable information for a human driven design process, so this method demands that the user be skilled in computational practice, in order to effectively interact with the computerâ&#x20AC;&#x2122;s system. The output visuals for these methods are typically a compromise between how a computer can store and display information, and the ways a human can understand it. So, as an example, rather than showing all of the points with good views in a certain direction, a user would specify a certain sized set of points with views in a direction, cross reference that with program, circulation paths, etc. and output a voxel grid of best points for a given function. In an interactive visualization, this process would simply allow the user to query information rather than interact directly with it.

Data modelling is both a linear and lateral process, in which the breadth of information must be related before specific derivations can occur. It is important to remember that, while the final data used to generate visualizations is specific, the entire data model is still accessible for investigation at any point and non essential information is still represented. The steps for relating datasets in the most comprehensive manner depends on a specific data instance, as well as the specific nature of relationships. Building the general data model is relatively simple: interpret data, find commonalities, locate additional data (how do specific sets relate), build connections. The construction of the specific site based architectural derivative model will be described here in greater detail, as an example. Depending on the quality of data available (Los Angeles has a very high quality public data collection program) the process and results may be significantly different than those presented here. The first step after the general data model has been assembled is to begin site discovery and hard boundary definition. The hard boundary model uses a set of data including legal, zoning, ownership, historical stock, existing buildings, etc. The final model will delimit the precise volume in which the project can be built.

DATA MODELLING

The next step is to define the series of relevvant site data that further limits the buildable area. These items include necessary infrastruccture, easements, planting, topography, and economic considerations.

Next a grid of points is created within the hard boundaries volume, and excluding those within the soft boundaries volumes. This will leave a series of points on the site which will be analyzed for the performative qualities. The grid size will determine the granularity of the data model, however the more granular the model, the more time it will take to analyze and work with themodel. This model used a relatively granular (when compared to a typical architectural site analysis) 20 foot by 20 foot by 20 foot grid. The size of the site was the biggest driver for this decision, as this grid left 13,000 individual points which needed to be analyzed.

AVAILABLE POINTS []

Each of the points is then evaluated for a series of architecturally relevant qualities which are derived from the larger datasets. The main issue under investigation, aside from analyzing the general data model more comprehensively, is the simultaneous visualization of all of these factors. Neither static (including animated), nor interactive visualization is sufficient to clearly represent this information. Imagine trying to understand the patterns occuring in 13,000 interrelated diagrams like this simultaneously, this is precisely what must be dealt with in the visualization. This is a clear example of the trait of n-dimensionality.

N-DIMENSIONAL POIN

Each of the 42 traits evaluated for each of the 13,000 possible points was derived through a data model of which this process is an example.

CENSUS DATA [POPULATION, DEMOGRAPHICS, LOCATION]

This model is for the natural circulation on the site, which shows the paths individuals would naturally take from one transit access point to another, based upon human behavior and transit usage information. The process for building the model is this: 1. Map the population of Los Angeles, and the related demographics. 2. Map the routes of various transit types in Los Angeles. 3. Map all of the stops, and relate them to their stop times, and the routes travelled. 4.Cross-reference this with Census information on journey to work, which includes demographically specific numbers of travellers, who commute a specific distance, on a specific type of transit, and leave at a specific time. 5. The projected number of users arriving at a given onsite stop, at a given time are used to drive a simulation of human behavior based agents travelling from one stop to another, at a given time during the day. Although this data model may not be empirically accurate, in a real project subject matter experts would help to build these models in a way which would accurately predict the information.

ROUTE DATA [HIGH SPEED RAIL LINE, SUBWAY LINE, METRO LINE, BUS LINES]

STOP DATA [STOPS, ROUTE ORDER, TIMES, TRIBUTARY AREA]

STOP LOCATIONS [SITE, STOPS, TOPOGRAPHY, ON-SITE BUILDINGS, NUMBER OF TRANSIT USERS PER STOP TYPE PER TIME]

CIRCULATION MODEL [NUMBER OF TRANSIT USERS PER TIME PER TYPE, HUMAN BEHAVIOR MODEL, LOCATIONS]

VISUALIZATION EXPERIMENTS The experiments to follow demonstrate a series of visualization strategies which seemed to be best suited for the types and quantities of data that has been gathered. The visualizations in this book are not the actual visualizations used, rather, they are static representations of different aspects of the visualizations which are actually located and connected within the data model. The full data model can be analyzed, adjusted, investigated, added to, or subtracted from dynamically. Additionally, these visualizations allow for change in view, magnification, and element isolation to almost any extent needed. Three visualization methods have been investigated, and architectural (formal, spatial, and/or functional) imaginations have been pursued, in an attempt to understand the architectural implications of those different methodologies. Many more visualization methods, or further developed versions of these are likely possible, but this first step should demonstrate the extent to which these representations influence design. All of these methods capitalize on integrated visualization strategies, as these strategies have been shown to be the best possibility for complex, high-dimensional datasets of large quantities. Static and interactive visualizations were also created, however, these visualizationâ&#x20AC;&#x2122;s architectural implications were not evaluated here. Further, the architectural investigations are intended to engage the intuitive aspects of the design process as little as possible, relying on strictly data informed decisions, in an effort to determin how information is used in design.

VOXEL

The voxel based visualization method takes the mapped points and stores their various qualities within them, visualized as a series of pixels. These qualities cannot be visualized in a static manner and must be a part of an integrated visualization. The data itself is manipulated in order to create a visualization model with best (most useful, having the desired qualities) voxels isolated. Voxel based visualization was used in two design experiments, one which translates the voxels into design elements, with additional elements drawn from contextual data and third generation derivatives. The second continually granulates the voxels to provide a much higher resolution pixel model which could represent an architecture.

NETWORK / TOPOLOGICAL

The network or topological model uses the mapped points and connections between them to determine critical points and topological networks that surround them. The architectural experiments undertaken for this visualization type capitalized on two separate aspects of this type of visualization. The first uses the topologized mesh to generate formal and spatial qualities. The second uses linear network elements spatialized with very simple elements.

FIELD

Field based visualizations map information similarly to voxel viualizations in that each trait is mapped and able to be accessed separately, or in tandem. They are opposites, however in the way that the information is computed; specifically, voxels use discrete information with one value per voxel, while the field is computed as a continuous entity, with every possible location having itâ&#x20AC;&#x2122;s own qualities. This means that the areas between each point are extrapolated from surrounding points. This method demands more computational power, but provides more granular results.

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The building massing is located by the specific driving characteristic of each programmatic area, and located based upon the applicable datasets. This massing takes into account a variety of different data dimensions, yet some require further development to engage effectively, with things like fenestration, opening orientation, structural placement, and more granular formal and spatial development.

VOXEL BASED VISUALIZATION

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CONCOURSE The concourse is dependent upon circulation and paths between the series of access points.

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ACCESS POINTS The platforms are dependent upon their connection to transportation lines, and thus needed to be sited as close as possible. That data is cross referenced with the programatically necessary dimension for each platform. for many this would include sun access, views, circulation, etc.

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OTHER PUBLIC FUNCTIONS These functions typically organize themselves around the concourse areas, however, available points are analyzed for sun and views, access to other program, circulation, etc. before being chosen. Further program information is used to generate height for these areas as well as the amount of different regions of each type and their sizes. This Frame: WAITING

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ARCHITECTURAL EXPRESSION Views of the site are cross referenced with the massing locations, to find the ost promising areas for exterior architectural expression. This information could inform a designer to concentrate their exterior focus on these areas.

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VERTICAL CIRCULATION Vertical circulation locations were found by finding the points in each area that passed through the most points. The areas had been decided by general areas and distance from emergency exits as well.

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ESCAPE ROUTES Escape routes were located to find the shortest paths from the access to the public right of way which are clear and direct. If more emergency escapes were needed per particular areas, they were added where paths were a bit longer.

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SOLID CIRCULATION PATHS Solid circulation paths have been determined by reassessing the circulation through the new mass. Views have also been used to determine this, in conjunction with connection to program, emergency exits, vertical circulation, and sun access.

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CIRCULATION VOIDS The voids have been determined in conjunction with circulation solids, however, these areas will be evaluated against sun direction data to locate the best points for voids.

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POSSIBLE VERTICAL STRUCTURE By finding every point with an uninterupted path to the ground, vertical connection possibilities are taken into account. working with engineers to embed deeper structural derivitaves into the analysis would allow for more accurate and powerful structural analysis.

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VOXEL BASED VISUALIZATION The voxel based visualization’s inherently spatially pixellated expression lends itself to forms and spaces with orthogonal qualities. The discreteness of each voxel is one of the method’s defining characteristics, and can be, to some extent, felt in the formalization. The programmatic and performative methods that have been used in this implementation mean that this architecture is relatively better at these aspects, while it is lacking in expression and spatial quality. The overtly orthogonal and highly complex forms and spaces implied by the voxel method demand that the designer engage with the information, in order to start creating effective architecture, and outside information should be engaged with. For instance, one could define a structural unit based around the voxel, and use the information in the viualization to drive that model. Another method might be to begin defining contextual geometries which could be pushed through the visualization, in order to create a manifestation which suits its surroundings. This experiment draws on very basic contextual geometry (lines and planes) from the Union Station and Patsaourus Bus Terminal in order to provide continuity with those buildings and a counterpoint to the pixelated forms of the visualization. It was defined through the programmatically driven definition of a series of spaces shown throughout this section. The specified regions are used, with as little additional intuitive design as possible, to locate specific spaces inside the ‘building,’ and to provide formal implications. Despite perhaps lacking full architectural definition, the forms and spaces do have a complex character which was not intentionally created by the designer. This potential to find or discover implications which generate quality from the information, is very interesting. Indeed, it might allow for a much more impactful design, as the performative and spatial vertebrae which is realized through more architectural means.

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Topological visualization methods vary in their specific implementations, but typically involve the generation of a networked visualization of a given information set and its critical points. The process of discovering critical points in data can be udnertaken in a variety of ways, but typically involves using a commplex equation to represent the relativity of given pieces of information. The computerâ&#x20AC;&#x2122;s role in these visualizations revolves around the processing of those critical points, and the algorithmic connection of related points. The example presented here allows for the designer to dynamically control the relative importance of various factors in the design, in order to discover design solutions with different qualities maximized.

TOPOLOGIC VISUALIZATIONS

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These topological visualizations have strong implications for form and space, as they are inherently spatial. They allow for a access to large, multi-dimensional datasets. although much of the processing of those datasets is not visual, only the outcome is. It is possible that these topological analyses are the foundation for some parametric practice, as they push the design towards topologized, smoothed forms which can be garnered from the network.

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The process for this specific implementation begins with the creation of a minimization formula which relates all factors parametrically. The spcific formula for this option is the maximization of all influencing factors. The network was separated based upon the relative heights of the points, so if there are two points directly above one another, they enter a separate dataset, each of which is analyzed separately in order to obtain the networks. Although any number of topological network algorithms could have been used to determine network qualities, these topologies used a delauney algorithm to do so. Long network links are disposed of, as these connections are weaker than close connections, resulting in dual minimized networks, which can be joined, and smoothed to create a simple form. Interior highly programmatic spaces are determined by specific programatic needs, leaving excess space for circulation and additional program (see next page).

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Spatial and formal networks resulted in highly varied spatial conditions, allowing for both strictly programmed and more flexible spaces. While more effort would need to be undertaken to design a working building, this prototype demonstrates the varied, yet interconnected spatial qualities demonstrated in the topological network visualization.

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The separation between flexible and programmed spaces, and the spatial and formal aspects of the design create interesting qualities. Simple processes result in a relatively interesting form, and more design work could push the outcome into a strong innovative design.

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Another possible result from topological network visualizations capitalizaes on the connective aspect of the network, rather than its topological nature. This exploration used individually maximized networks, so one network for views, one for sun, one for access, etc. and removed the topologies, leaving a series of linked networks. The connections between various points become spatail and formal items, and a series of expressive elements are added, where called for by views and performance. Although this imaginary result was generated quickly, and lacks a distinct functional nature, it shows the very intterconnected qualities of the visualization. Additionally, this experiment demonstrates how the choice of inluencial information can have a major impact on the outcome of the design.

NETWORK VISUALIZATIONS

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A field visualization is in some ways the opposite of a voxel visualization, in that it represents data as a continuous gradient, or set of gradients, rather than a series of discrete elements. This allows for an even higher granularity of data, and a new raft of methodologies like field lines or continuous transformations to be effective.

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The final visualization on this page shows a field lines (streamline) visualization, with seeding points at each of the points of access to various infrastructure (transit platforms). Program data is used to define the size of an object which is composed of a semi-random set of contextually derived planes, drawn from the historic Union Station Building, as well as the patsaourus bus terminal. Lines of connection between the various program objects are pulled through the areas with the most performative quality. For the architecturalization of the field lines, the object faces they pass through are connected using the lines as a guide, elements are added based upon orientation, views and sun access. This quick experiment had no additional intervention by the designer, but does promise some interesting spatial and formal qualities, with some more direct and intuitive design engagement.

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The continuous nature of the field visualization also lends itself to highly randomized compositions, which can be driven with specific data regardless of seed points. The ability to define a different proportional system to the one which is used by the pure data is a strong quality of field visualizations. An interesting method might be to derive a system of elements, proportions, structures, etc. and drive their implementation with field data, which can be localized to any given point, rather than the discrete voxels. This implementation generated data based rectangular prisms in a more experimental exploration of the amount of complexity which can be generated with minimal input or formal variation using field data.

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C H A P T E R

ANALYSIS + IMPLICATIONS + AREAS FOR FURTHER INVESTIGATION + CONCLUSION

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A N A L Y S I S PRACTICAL

The first and most explicit matter for analysis is the comparison between the existing design for the extension of Union Station, and the proposal implicated by the voxel visualization experiment in this thesis. The traits analyzed are a small subset of the data analyzed, but represent those for which the existing design has diagrams, and thus should have been taken into account in their design. The blue and green bars represent the performance of the voxel proposal, while red and purple bars represent the existing design. It is clear that the proposal outperforms the existing design, in regards to these attrbiutes, although this should not be surprising, as they specifically drove the thesis design, while many other factors, including economy, likely drove the existing design. Regardless, the fact that this method can improve certain conditions in a design should be regarded as a successful fulfillment of the practical side of this thesis. Indeed, a methodology has been provided which allows for the successful incorporation of more information into the design process, in a way which allows a designer to accurately engage that larger quantity of information and make successful design choices. The process has also been automated, to a large extent, which means that this method could be quickly implemented in any or every project for which data is available. As such, it is possible to use this method to provide an informational framework on which to begin design work, and which could be used in conjunction with traditional architectural information analysis techniques. Additional datasets could, and should, be added to those analysed in this thesis, so as to further the goals of the comprehensive data model. With large data collectors like social networks, google places, etc. there is likely a wealth of data available to those who have the impetus to use it. Likewise, the use of artificial intelligence to analyse that information would likely have provided much stronger results, and should be a focus for future investigations. As previously mentioned, the data models built could have been more empirical, and should be, if incorporated into real architectural projects.

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ARCHITECTURAL

The architectural results of this thesis were mixed. While it seems that information analysis does, to some extent, hold implications for architectural manifestations, the direct mining of these manifestations from the visualization methods themselves was not adequately investigated. This was likely due to the focus on the practical aspects of the thesis, which, as the factors which directly adress the thesis problem, was more thoroughly investigated. Many architectural implications may lie within the dat visualization theory which serves as the foundation of static and interactive visualizations, which were not investigated much here. The specific implications for the voxel experiment were interesting, because they are volumetric and translate relatively simply into architecture. The form and space created were relatively complex, when compared to much of the diagram driven architectures. By this I mean that more axes, interconnected spaces, interspersal of interiority and exteriority, etc. occurred. The issue is that much work was left before an actual architectural formulation could be arrived at, much of which could not be driven by the specific sets of data which I used to inform the design. Indeed, the most dynamic and interesting pieces of the architecture occured when contextual geometric data was used to drive the expression of the spatial information from the visualization. The toplogical visualization gives highly varied spaces, and an interesting form to space relationship, at least in this project. There is potential there for an easy translation between the visualization and a smooth architecture like some of those produced by architects who do use network and topological visualization ostensibly. Again, much intuitive work would need to be done, before a fully coherent architectural expression was formed. However, the use of this as a foundational visualization upon which more work is built has potential. The network visualization experiment was very simplified and may or may not be deemed an architecture, although I would posit that it is architectural. This experiment featured a more intuitive processing of the data to drive a simple outcome, which nevertheless had an enormous amount of complexity. By iteratively driving a logical expressive system with a visualization system like this, very interesting architecture could arise. The field visualization, utilizing the stream lines also had some interesting qualities. However, more work would be needed to determine whether that architecture could

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work as more than a purely spatio-formal object (would it perform). Additionally, organizing the direct output would likely have solved many of the issues apparent in the experiment. Embedding further systems of logic which engage with this system also seems like it could have serious potential. While the experiments pursued here do show some promise, it is mainly as foundational assets upon which other sets of architectural logics should be built, and as drivers which could further refine those logics. Additionally, the visualization techniques which did not directly apply to the problem of visualizing large n-dimensional datasets were not mined effectively, and these may hold another set of implications for architectural research.

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1. Determinants like view, sun access or angles, etc. which are often sited as the rationale behind specific design moves.

I M P L I CAT IO N S This thesis has a series of implications in a variety of aspects relating to architecture. The most important implications, I believe, relate to the role of information in the design process, and the role of the architect or designer. While information and rationalization are typically seen as the basis of a design process, attempting to increase the information density of that process, while simultaneously attempting to engage in as few intuitive steps as possible has not been shown to directly enhance the architectural product. Rather, this thesis has shown that some determinants which have been sited as driving a design1 do not provide enough imperative to actually drive it. This means that simple responses to a given stimulus are not informed by the stimulus itself, but rather by a given designer. Put another way, the determinant is there, but the response is intuitive, it is not informationally grounded. Therefore, the typical rationalization process for a given design actually addresses very little of the real rationale behind a design. There is an opportunity then, instead of an architect focusing on recognizing and addressing performative issues, which have been shown to be inadequately addressed through traditional processes, but which can be quicly and accurately addressed through the methodology proposed in this thesis, the research and problem solving of a given architect should focus on the analysis and synthesis of architectural logics systems. These systems could be driven by the information provided, in order to create expressive and performative designs. The work of the architect, then, would be to research and design responses, using information, rather than using information to find locations for intuitive interventions. The potential for incorporation of big data into architecture has been shown to be not only possible, but very effective in addressing matters of architectural performance. The proposed method does provide a model for the possible enhancement of the architectural design process, and may allow for the kind of refocusing discussed above. Finally, the architectural implications of big data are interesting, but mainly because they provide patterns of information which are more complex than those typically able to be identified by architectural information analysis. While there may be some formal and spatial implications of big data for architectural form and space, a simple translation of visualization to architecture is not sufficient to locate them.

N E X T

S T E P S

The next steps in this process are likewise varied. The investigation of artificial intelligence and its pattern recognition capabilities could prove very powerful when used to find and analyze architecturally relevant data. Research on this front should be done in order to improve the practical aspects of this thesis. Another area which could improve both the architectural manifestation and the practical methods of this thesis is the incorporation of more and more varied datasets. Pulling Googleâ&#x20AC;&#x2122;s point of interest information, and cross referencing Facebookâ&#x20AC;&#x2122;s comments about that place, or Instagram photos which are located there could provide information about what kind of architectural elements a given society enjoys, as an example of the further possibilities. Combined with artificial intelligence, picture data could be analyzed to find contextual architectural trends which could be combined and synthesized to create an architectural logical system which could then be driven with the data driven method, in order to create a contextually based architectural project. Additional research should also be done on information culture, and the accompanying relevant expressive languages. Data visualization is one of those languages, but others may exist, and are culturally relevant markers for current populations. The development of that language should likely be addressed more fully than has been possible in this thesis, despite the early perception and intent to do so.

C O N C L U S I O N

In conclusion, this thesis should provide the necessary first step towards a more performative, relational, accurate method for engaging information in the architectural design process. The impact of the direct translation model of information visualization to architectural condition has been shown to be inneffective in regards to providing a full design solution. As such, the importance of architectural ordering, proportional, structural, material, etc. logics deserves a prime role in architecture, as the system of RESPONSES to a given ISSUE. This distinction, between issue and response is the larges single implication of this thesis, in that a method has been provided here for determining issues, which should effectively relocate the architectural focus of rationalization onto response.

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