A Method and Tool for Fact Type Reuse in the DOGMA Ontology Framework

  • Authors:

  • Christophe Debruyne;Pieter Leenheer;Robert Meersman

  • Affiliations:

  • Semantic Technology and Application Research Laboratory (STARLab), Department of Computer Science, Vrije Universiteit Brussel, Brussels, Belgium B-1050;Semantic Technology and Application Research Laboratory (STARLab), Department of Computer Science, Vrije Universiteit Brussel, Brussels, Belgium B-1050;Semantic Technology and Application Research Laboratory (STARLab), Department of Computer Science, Vrije Universiteit Brussel, Brussels, Belgium B-1050

  • Venue:
  • OTM '09 Proceedings of the Confederated International Conferences, CoopIS, DOA, IS, and ODBASE 2009 on On the Move to Meaningful Internet Systems: Part II
  • Year:
  • 2009

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Abstract

In the DOGMA approach to ontology engineering, the construction of an ontology starts from a "Lexon Base", a possibly very large and un-interpreted base of plausible elementary fact types called lexons. Lexons - mined from various linguistic sources such as schemas, texts or domain experts - are used to create ontological commitments by selecting or reusing a meaningful set of lexons and together with constraints so that the intended conceptualization is well approximated. All too often, the same or similar lexons are entered in the Lexon Base, which causes heterogeneity among different ontological commitments. Due to this heterogeneity, meaning negotiation to agree upon a common commitment becomes more difficult. Encouraging lexon reuse by providing knowledge engineers and domain experts an automated process for finding relevant lexons in the Lexon Base or existing ontological commitments can tackle this problem. In this paper, we introduce a novel approach to fact type reuse that we will apply to DOGMA MESS, a state-of-the-art collaborative ontology engineering methodology. The method we propose uses several heuristics that reside in one of the six semiotic levels described by Ronald Stamper's semiotic ladder and adds a pragmatic and social layer onto the current methodology and tools. We provide a proof of concept by implementing our method in a tool for finding relevant lexons while building an ontological commitment in a production environment called DOGMA Studio Workbench.