RDFKB: efficient support for RDF inference queries and knowledge management

  • Authors:

  • James P. McGlothlin;Latifur R. Khan

  • Affiliations:

  • The University of Texas at Dallas, Richardson, TX;The University of Texas at Dallas, Richardson, TX

  • Venue:
  • IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
  • Year:
  • 2009

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Abstract

RDFKB (Resource Description Framework Knowledge Base) is a relational database system for RDF datasets which supports inference and knowledge management. Significant research has addressed improving the performance of queries against RDF datasets. Generally, this research has not addressed queries against inferred knowledge. Solutions which do support inference queries have done so as part of query processing. Ontologies define the rules that govern inference for RDF datasets. These inference rules can be applied to RDF datasets to derive additional facts through methods such as subsumption, symmetry and transitive closure. We propose a framework that supports inference at data storage time rather than as part of query processing. The dataset is increased to include all knowledge whether explicitly specified or derived through inference with a negligible overhead. Queries against inferred data are simplified, and performance is increased.