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Spatial database design is very important in the development of planning support systems, since a GIS system must be built on standard components. The components start from spatial database as the foundation, then editing, analysis, simulation, and finally visualization. However, the design methodology of spatial database hasn’t been developed adequately in urban research compared with the predictive modelling and simulation. This argument is strengthened by the minimum findings of the similar PhD theses currently researching data modelling for urban design. One of them is currently pursuing on “Object-Oriented Data Modelling and Warehousing to Support Urban Design” (Koshak & Flemming, 2002). Another research is pursuing on “Restructuring UrbanSim Model into ArcGIS (Geodatabase) Data Model using UML” (Kyuwon Park, 2002), which emphasized on land-use dynamics simulation modelling of the well-known UrbanSim planning model. Judging from the minimum research efforts in this area, we argue that data modelling is still a new area in urban design research.

In the past few years, data models for editing and managing urban information have largely been in the province of specialized computer aided design (CAD) tools used by engineers and architects. This combination of data modelling in GIS, Spatial Data Engine (SDE), through UML or XML format as bidirectional medium, provides a potential for managing virtually unlimited amounts of details representing many aspects of the built environment of the entire city, along with different future or past scenarios. Cote argued that data models for representing the relationships between buildings and their components have yet to be developed for an object-relational system (Cote, 2002). He perceived the urgent need of an appropriate data model when he was confronted by several problems while developing an agenda “towards modelling broad scale urban scenes in an object-relational database”. The first problem is how to associate primitive shape objects to represent built-environment, i.e. buildings. A representation of a building is usually composed of different features, such as points, lines and polygons. Relationships in the spatial database, such as “the windows, associated with hotel rooms, which have a view of the natural gas tanker”, are examples of information that may be desired from a good urban data model. The second problem is the need for data models, which are interoperable between GIS and CAD. These are the problems that can only be solved through data modelling.

In the next section, the paper will introduce data modelling of urban design guidelines. Most guidelines consist of clear regulatory and advisory statements of design rules and relational rules between design objects. The paper will explain how urban design guidelines can be modelled into data models, which in turn will create spatial database capable of enforcing the guidelines in the design process.

3. Urban Design Guidelines
To implement data modelling in the development process of spatial database for urban design, urban design guidelines were chosen as modelling case study. It is because they contain clear statements of desired relationships and rules between urban objects, available to public. They act as a guide for developers and designers, and possibly other agents, in planning and designing development, prepared by local authorities with the participation of landowners, developers, partnerships, business, and community organizations (Cowan, 2002). They are either the result of negotiated agreements between stakeholders or a direct guidance from local planning authority. They can be used to identify and develop performance criteria to measure effective plan execution through performance-based standards (CONCERN, Inc. et al., 2002).