Similarity-Based Information Retrieval and Its Role within Spatial Data Infrastructures

While similarity has gained in importance in research about information retrieval on the (geospatial) semantic Web, information retrieval paradigms and their integration into existing spatial data infrastructures have not been examined in detail so far. In this paper, intensional and extensional paradigms for similarity-based information retrieval are introduced. The differences between these paradigms with respect to the query and results are pointed out. Web user interfaces implementing two of these paradigms are presented, and steps towards the integration of the SIM-DL similarity theory into a spatial data infrastructure are discussed. Remaining difficulties are highlighted and directions of further work are given.