Representing Partial Spatial Information in Databases

In this paper we present a spatial data model which facilitates the representation of and reasoning with various forms of qualitatively and quantitatively incomplete spatial information. The model is founded on a combination of object-oriented and constraint-based data modeling facilities and provides for representations of variable precision and granularity. We identify four basic reasoning tasks required for query processing operations and outline algorithms for each task. Finally, we discuss extensions of the model and outline an implementation based on the Telos knowledge base management system extended with an appropriate constraint reasoning component.

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