Document Type
Presentation
Publication Date
12-2009
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.
Repository Citation
Jain, P.,
Henson, C. A.,
Sheth, A. P.,
Yeh, P. Z.,
& Verma, K.
(2009). SPARQL Query Re-Writing for Spatial Datasets Using Partonomy Based Transformation Rules. .
https://corescholar.libraries.wright.edu/knoesis/667
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Presented at the Third International Geospatial Semantics Conference, Mexico City, Mexico, December 3-4, 2009.
Paper presented in tandem with the presentation can be found at http://dx.doi.org/10.1007/978-3-642-10436-7_9.