Abstract
Often the information present in a spatial knowledge base is represented at a different level of granularity and abstraction than the query constraints. For querying ontology’s containing spatial information, the precise relationships between spatial entities has to be specified in the basic graph pattern of SPARQL query which can result in long and complex queries. We present a novel approach to help users intuitively write SPARQL queries to query spatial data, rather than relying on knowledge of the ontology structure. Our framework re-writes queries, using transformation rules to exploit part-whole relations between geographical entities to address the mismatches between query constraints and knowledge base. Our experiments were performed on completely third party datasets and queries. Evaluations were performed on Geonames dataset using questions from National Geographic Bee serialized into SPARQL and British Administrative Geography Ontology using questions from a popular trivia website. These experiments demonstrate high precision in retrieval of results and ease in writing queries.
The evaluation components related to this work are available for download at http://knoesis.wright.edu/students/prateek/geos.htm
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Jain, P., Yeh, P.Z., Verma, K., Henson, C.A., Sheth, A.P. (2009). SPARQL Query Re-writing Using Partonomy Based Transformation Rules. In: Janowicz, K., Raubal, M., Levashkin, S. (eds) GeoSpatial Semantics. GeoS 2009. Lecture Notes in Computer Science, vol 5892. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10436-7_9
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