Automatic Semantic Transformation between Geo-Ontologies

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The overall project aims at developing techniques for the semantic integration of geospatial data sets. In order to do so, correspondences between different domain ontologies have to be defined. Currently, this is typically done manually, as without prior knowledge it is difficult if not impossible to identify correspondences. In this proposal we want to investigate and exploit geometric cues (plus topologic and semantic ones) to infer semantic correspondences. The following hypothesis is made: object descriptions relate to the same phenomenon when they either describe spatially similar objects (i.e. objects at the same spatial location), or if they have similar geometric characteristics.In the first phase the focus was laid on the integration of data of the same location with similar geometric and semantic resolution. The research in the second phase will relax these restrictions in two ways: 1) integration of data sets of different location,2) integration of data sets of different resolution.In order to derive the necessary comparable object instances, in the first case classification rules based on geometric and topologic characteristics will be determined. In the second case, generalization rules will be applied. As a method to derive the correspondences ¿ especially the hierarchical correspondences ¿ we will use association rules from Data Mining.