Methodical Spatial Database Design with Topological Polygon Structures

Methodical Spatial Database Design with Topological Polygon Structures

Jean Damascène Mazimpaka (National University of Rwanda, Rwanda)
DOI: 10.4018/978-1-4666-2038-4.ch019
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Abstract

Spatial databases form the foundation for a Spatial Data Infrastructure (SDI). For this, a spatial database should be methodically developed to accommodate its role in SDI. It is desirable to have an approach to spatial database development that considers maintenance from the early stage of database design and in a flexible way. Moreover, there is a lack of a mechanism to capture topological relations of spatial objects during the design process. This paper presents an approach that integrates maintenance of topological integrity constraints into the whole spatial database development cycle. The approach is based on the concept of Abstract Data Types. A number of topological classes have been identified and modelling primitives developed for them. Topological integrity constraints are embedded into maintenance functions associated with the topological classes. A semi-automatic transformation process has been developed following the principles of Model Driven Architecture to simplify the design process.
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Introduction

With the current advances in Information and Communication Technology, there has been a problem shift from data availability to data maintenance. A database is a large, structured and integrated collection of data. A Database Management System (DBMS) is a software system used to create and manage databases. Today’s best approach to managing huge amounts of data is to use a DBMS. The field of Geographic Information Systems (GIS) makes no exception. However, in GIS the problem becomes much more complex due to the nature of spatial data that make a spatial database (Tveite, 2001). A spatial database is a special type of database which, in addition to containing conventional attribute values of the objects, contains data about their geographic location and shape. In the field of spatial database development, a lot of work has been done to capture the semantics of spatial objects such as their geographic location and shape (Shekhar et al., 1999). However, less importance has been given to capturing their spatial relations. For instance, spatial objects such as provinces of a country can be modelled as polygons and their geographic coordinates are recorded to indicate their geographic location. However, their spatial relations that they cannot overlap and they form a contiguous area which is the country, are not modelled or it is done in an inflexible way if done. These spatial relations will later form database integrity constraints that need to be maintained. The spatial integrity constraints of the objects are among the most important problems in modelling spatial databases (Shekhal et al., 1999). These considerations highlight the need for a mechanism to capture spatial relations, and an improved methodology for spatial database design which considers the maintenance of spatial integrity constraints throughout the database development cycle.

Egenhofer and Franzosa (1991) distinguish three categories of spatial relations; topological relations, metric relations and relations concerning the partial and total order of spatial objects. Topological relations are spatial relations that are not affected by elastic transformations such as rotation and scaling (Egenhofer et al., 1994). This paper presents an improvement to existing spatial database design methodology by including also topological relations in the conceptual model of the database. Through a semi-automatic transformation process, topological relationships are carried at all design steps till the implementation where they become database integrity constraints that are enforced using a set of maintenance functions. The work presented in this paper focuses on collections of area features that display topological dependencies. The paper is structured as follows; after this introduction, we present an overview of currently existing approaches of data modelling in spatial databases. Next, we describe the proposed spatial database design methodology. To show the applicability of the proposed approach, we then present an example of implementing the proposed transformational design. Finally, we give some conclusions and the direction for future work.

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