CHAPTER 3
GIS DATABASE DATABASE DATA MODEL CREATING DATABASE ADVANTAGES OF GIS DATABASE
Database Data Models There are a number of different database data models. Amongst those that have been used for attribute data in GIS are the: • Hierarchical • Network • Relational - RDBMS • Object-oriented - OODBMS • Object-relational - ORDBMS
Hierarchical Data Model •
The Hierarchical Data Model is a way of organizing a database with multiple one to many relationships. The structure is based on the rule that one parent can have many children but children are allowed only one parent.
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Definition: - hierarchical database organizes data at different levels and use one - to- many associations between levels.
Network Data Model • The network model is a database model conceived as a flexible way of representing objects and their relationships. Its distinguishing feature is that the schema, viewed as a graph in which object types are nodes and relationship types are arcs, is not restricted to being a hierarchy. • Definition: a networks database builds connection across tables of data.
Relational Data Model • Relational data model is the primary data model, which is used widely around the world for data storage and processing. This model is simple and it has all the properties and capabilities required to process data with storage efficiency. • Definition:- A relational database is a collection of tables or relation that can be connected to each other by keys. In GIS, the key often has the same name such as ID.
Cont..
Cont.. • Most popular type of DBMS – Over 95% of data in DBMS is in RDBMS
• Commercial systems – Microsoft Access – Microsoft SQL Server – Oracle – IBM DB2 – Informix – Sybase
Object-relational Data Model • The object-relational data model extends the relational model by providing system including object orientation and add constructs to relational query languages to deal with added (complex) data types, such extensions attempt to preserve the relational.
Object-oriented Data Model • A data model is a logic organization of the real world objects (entities), constraints on them, and the relationships among objects. • In the object oriented data model the both data and their relationship are contained in a single structure known us an object. • An object includes information about relationship between the facts within the object, as well as information about its relationship with other objects.
Creating Database • Database design and implementation are guided by the relationships between the data to be stored in the database. • The database design process is concerned with expressing these relationships, then implementation with setting up a new structure for these relationships within the chosen database software. • The stages of database creation are summarized: Oxborrow (1989)
Reeve (1996)
Data investigation
Needs analysis
Data modelling
Logical design
Database design
Physical design testing
Database implementation
Implementation
Database monitoring
Maintenance
Data investigation: • Is the ‘fact finding’ stage of database creation. • Here the task is to consider the type, quantity, and qualities of data to be included in the database. The nature of entities and attributes is decided. Data modelling: • The process of forming a conceptual model of data by examining the relationships between entities and the characteristics of entities and attributes. This stage, like the data investigation stage, can be carried out independently of the software to be used.
Database design: • The creation of a practical design for the database. • This will depend on the database software being used, and its data model. This is the process of translating the logical design for the database (produced during the data modelling stage) into a design for the chosen DBMS. Field names, types, and structure are decided. In practice, the design will be a compromise to fit the database design model with the chosen DBMS. Database implementation: • The procedure of populating the database with attribute data, and this is always followed by monitoring and upkeep, including fine tuning, modification and updating.
Advantages of GIS database Reduction in data redundancy Maintenance of data integrity and quality Data are self-documented or self-descriptive - information on the meaning or interpretation of the data can be stored in the database, e.g. names of items, metadata Avoidance of inconsistencies - data must follow prescribed models, rules, standards Reduced cost of software development - many fundamental operations taken care of, however DBMS software can be expensive to install and maintain Reduce maintenance cost – better data organization and reduce data duplication Security restrictions - database includes security tools to control access, particularly for writing
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Data transferred – user knowledge can be transferred between application easily - database remain constant
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Improve data sharing – data can be provided to multilevel of users (manager, officer, public user, etc)
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DBMS – better able to manage large number of data
DISADVANTAGES: •
The cost of acquiring and maintaining DBMS software quite high
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DBMS add complexity of managing data especially in small project