A deductive object - oriented approach to Geographic Information Systems
Vilas Wuwongse, Wiboon Promphanich
Division of Computer Science Asian Institute of Technology
P.O. Box 2754, Bangkok 10501, Thailand
Abstract
This paper aims at proposing a deductive object-oriented data model which is suitable for the specific characteristics and requirements of geographic information system (GISs). A GIS involves the creation, storage, retrieval, browsing and management of electronic from of map entities. In the proposed data model, spatial entities are modeled as an instance of subclass of classes point, Line, and Polygon. Spatial entities in harit properties of their super classes apart from their own properties. These spatial entities are associated with maps. The other type of maps is overlay which is derived from other existing maps derived from other existing maps. The overlay is modeled as rules which are the intentional part of GI.
The model provides a language for data. Definition and manipulation. The language is a modification of SQL and includes commands for the user to create, insert, delete, and update both the data and the rules.
Introduction
A geographic information system (GIS) can be viewed as a database system in which most of the data are spatially indexed [ SMITH et. al., 1987] . Associated with this database is a set of procedures which are operated in order to answer queries about spatial entities in the database. Data stored in GIS may be represented on one of the three basic types of maps, i.e. cartographic, thematic and topographic maps. This paper concerns with thematic map GIS.
Thematic maps consist of closed regions. Each region is associated with an attribute. For example, a soil map would associate each region to a particular soil type. Land-use and zoning maps used in urban planning are other examples of thematic maps. Partition maps. They have the additional property that there is a one-to-one mapping from the set of regions to the set of attribute values.
One of the important steps in designing a GIS is the selection of a data model because the model will determine how the data can be represented, stored and utilized. Three major data models which have been proposed for GIS are relational, deductive and object oriented data models. [ van ROESSEL, 1987; TRINIDAD, 1990; WORBOYS, et al., 1990] Even though it has been very successful in business applications, the relational data model has limited representational capability. The relational data model only a allows data to be represented in terms of records which is a set of certain field. Complicated data cannot readily be expressed as records. Deductive and object oriented data models extend the relational model by allowing complex data to be represented as intensional rules and classes or objects, respectively. The intensional rules of the deductive data model and the inheritance mechanism of the object-oriented data model also helps reduce redundancy in data representation.
This paper proposed and develop a deductive object-oriented data model ( DOODM ) for GIS. The model combines the advantages of both deductive and object-oriented data models. Under the model, GIS entities and characteristics are readily and efficiently represented. The remainder of the
Paper is organized into four sections. Section 2 describes requirements of GIS Section 3 gives the details of the proposed data model while section 4 a brief description of a prototype GIS implemented. Section 5 draws conclusions.
Requirements of GIS
The research of [ GALKINS, 1983; PEUQUET, 1984] adopted by [ SMITH et. al., 1987 ] suggests that the following general requirements should be satisfied in the design and implementation of GIS:
- ability to handle large, multilayered, heterogeneous data bases of spatially indexed data;
- ability to query such data bases about the existence, location and properties of a wide range of spatial objects;
- efficiency in handling such queries that permits the system to be interactive;
- flexibility in configuring the system that is sufficient to permit the system to be easily tailored to accommodate a variety of specific applications and users;
- ability of the system to ' learn in a significant way about the spatial objects in its knowledge and data bases during use of the system.
The data Model
1 GIS and DOODM
DOODMS represent data and their relationships in terms of objects / classes and aggregation / association / generalization / rules respectively. Complex data can be expressed by means of object / class representation while reduction of redundant data materialized by means of generalization and rule representation. There are three common data types on GIS, i.e. explicit, virtual and display data types. They can all be represented under DOODMS.
There are two types of the explicit data type: primitive and complex types. Example of primitive types are INTEGER, REAL, CHARACTER, etc. These primitive types could be used to represent attributes of complex types, e.g. INTERGER representing the number of rooms which is an attribute of building objects. Examples of complex types are buildings which consist of geometric objects ( e.g. points, lines and polygons ) and other attributes ( e.g. number of rooms and height ). In our model, explicit data types are components of the base maps which are stored in the fact base or the extionional database.
The virtual data type is not explicitly stored in the database but is deduced from the explicit data. In the proposed model, the virtual data type represents derived maps and is stored in the rule base or the intensional database.
The display data type is composed or report and graphics subtypes. Both explicity and virtual data types can be displayed by report generators or graphic programs. This data type depends on the applications of the user, Therefore, in this paper we will not concern ourselves with this data type.
2 The GIS Extensional Database
Unlike other kinds of data used by most information systems, geographical data must include information about locations and attributes which are related to each other. All geographical data can be reduced t5o three basic topological constructs: points, lines and polygons ( areas ). For examples, roads and railways can be represented as lines, houses as points and soil-types as polygons. Each point or line or polygon may have attributes associated with it. For example, a road may have a name and a house an address. These geographical and attribute data types such as INTEGER and STRING.
2.1 Class Primitive
Primitive objects are provided by the system for the user to build more complex objects. Normally the class primitive includes classes CHARACTER, NUMBER, DATE, TIME, STRING, ARRAY, SET and LIST. In addition, there is a class
Specially defined for GISs, i.e. class Coordinate XY.
[ Definition 3.1. ] A Coordinate XY object is the aggregation of Coordinate X object and Coordinate Y object. Both Coordinate X and Coordinate Y objects are instances of class INTEGER.
The representation of Coordinate XY object is composed of integer, @ sign and integer. For example.
(1 @ 2 ) > point with x-coordinate = 1 and Y - coordinate = 2.
2.2. Class Geo Object
The Geo Object class is an abstract class representing the geographic description of spatial objects. This class is divided into three subclasses : Point, Line, and Polygon.
[ Definition 3.2] A point object is the aggregation of Id object and CoordinateXY object. A Pointed object is an instance of class STRING.
[ Definition 3.3] A line object is the aggregation of ID object and a list of CoordinateXY objects. A line object is the aggregation of ID object and a list of CoordinateXY objects. A LineID objects is an instance of class STRING. A list of CoordinateXY object is an instance of class LIST.
[ Definition 3.4] A polygon object is the aggregation of ID object A polygonID object is an instance of class STRING. A set of CoordinateXY objects is an instance of class SET.
