Efficiently querying relational databases using OWL and SWRL

  • Authors:

  • Martin O'Connor;Ravi Shankar;Samson Tu;Csongor Nyulas;Amar Das;Mark Musen

  • Affiliations:

  • Stanford Medical Informatics, Stanford University, School of Medicine, Stanford, CA;Stanford Medical Informatics, Stanford University, School of Medicine, Stanford, CA;Stanford Medical Informatics, Stanford University, School of Medicine, Stanford, CA;Stanford Medical Informatics, Stanford University, School of Medicine, Stanford, CA;Stanford Medical Informatics, Stanford University, School of Medicine, Stanford, CA;Stanford Medical Informatics, Stanford University, School of Medicine, Stanford, CA

  • Venue:
  • RR'07 Proceedings of the 1st international conference on Web reasoning and rule systems
  • Year:
  • 2007

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Abstract

For the foreseeable future, most data will continue to be stored in relational databases. To work with these data in ontology-based applications, tools and techniques that bridge the two models are required. Mapping all relational data to ontology instances is often not practical so dynamic data access approaches are typically employed, though these approaches can still suffer from scalability problems. The use of rules with these systems presents an opportunity to employ optimization techniques that can significantly reduce the amount of data transferred from databases. To illustrate this premise, we have developed tools that allow direct access to relational data from OWL applications. We express these data requirements by using extensions to OWL's rule language SWRL. A variety of optimization techniques ensure that this process is efficient and scales to large data sets.