Efficient RDF data management including provenance and uncertainty

  • Authors:

  • James P. McGlothlin;Latifur Khan

  • Affiliations:

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

  • Venue:
  • Proceedings of the Fourteenth International Database Engineering & Applications Symposium
  • Year:
  • 2010

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Abstract

RDFKB (Resource Description Framework Knowledge Base) is a solution for managing, persisting and querying semantic web knowledge. RDFKB provides a flexible data management schema that allows additions, deletions, and updates at all levels in the data model. RDFKB also supports 1) knowledge inference, 2) provenance and lineage, 3) probabilities and uncertainty reasoning, 4) trust factors, 5) dataset linkage and ontology alignment. We will show through a variety of use cases and experiments that RDFKB enables each of these tasks. We will also show that RDFKB outperforms all other semantic web repositories through experiments using 26 queries against 2 accepted benchmark datasets.