Instance-based matching of large life science ontologies

  • Authors:

  • Toralf Kirsten;Andreas Thor;Erhard Rahm

  • Affiliations:

  • Interdisciplinary Center for Bioinformatics, University of Leipzig, Germany;Dept. of Computer Sciences, University of Leipzig, Germany;Interdisciplinary Center for Bioinformatics, University of Leipzig, Germany and Dept. of Computer Sciences, University of Leipzig, Germany

  • Venue:
  • DILS'07 Proceedings of the 4th international conference on Data integration in the life sciences
  • Year:
  • 2007

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Abstract

Ontologies are heavily used in life sciences so that there is increasing value to match different ontologies in order to determine related conceptual categories. We propose a simple yet powerful methodology for instance-based ontology matching which utilizes the associations between molecular-biological objects and ontologies. The approach can build on many existing ontology associations for instance objects like sequences and proteins and thus makes heavy use of available domain knowledge. Furthermore, the approach is flexible and extensible since each instance source with associations to the ontologies of interest can contribute to the ontology mapping. We study several approaches to determine the instance-based similarity of ontology categories. We perform an extensive experimental evaluation to use protein associations for different species to match between subontologies of the Gene Ontology and OMIM. We also provide a comparison with metadata-based ontology matching.