Representing and Reasoning for Spatiotemporal Ontology Integration

Abstract

The World-Wide Web hosts many autonomous and heterogeneous information sources. In the near future each source may be described by its own ontology. The distributed nature of ontology development will lead to a large number of local ontologies covering overlapping domains. Ontology integration will then become an essential capability for effective interoperability and information sharing. Integration is known to be a hard problem, whose complexity increases particularly in the presence of spatiotemporal information. Space and time entail additional problems such as the heterogeneity of granularity used in representing spatial and temporal features. Spatio-temporal objects possess intrinsic characteristics that make then more complex to handle, and are usually related by specific relationships such as topological, metric and directional relations. The integration process must be enhanced to tackle mappings involving these complex spatiotemporal features. Recently, several tools have been developed to provide support for building mappings. The tools are usually based on heuristic approaches that identify structural and naming similarities [1]. They can be categorized by the type of inputs required for the analysis: descriptions of concepts in OBSERVER [2], concept hierarchies in iPrompt and AnchorPrompt [3] and instances of classes in GLUE [4] and FCA-Merge [5]. However, complex mappings, involving spatiotemporal features, require feedback from a user to further refine proposed mappings and to manually specify mappings not found by the tools.