SPARQL Query Re-writing Using Partonomy Based Transformation Rules

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 popu...

• Type: Conference
• Year: 2009
• Where: GEOS
• Authors: Prateek Jain, Peter Z. Yeh, Kunal Verma, Cory A. Henson, Amit P. Sheth
• Keywords: GEOS 2009, Information Management, Query Constraints, Spatial, Spatial Knowledge Base