An heavyweight ontology is a lightweight ontology (i.e. an ontology simply based on a hierarchy of concepts and a hierarchy of relations) enriched with axioms used to fix the semantic interpretation of concepts and relations. Such an ontology can be a domain ontology, an ontology of representation, an ontology of PSM, etc. In our work, we argue in favor of using a graph-based solution to deal with the different activities related to Heavyweight Ontology Engineering, in particular ontology representation, ontology operationalisation, ontology evaluation (i.e. verification and validation) and ontology matching. Our approach consists in using the graph-based paradigm to represent all the components of an heavyweight ontology (i.e. Concepts, Relations and Axioms) and using graph homomorphism techniques to compare (at the conceptual level) the core components of an heavyweight ontology: the Axioms. This explicit graph-based representation of axioms coupled with reasoning capabilities based on graphs homomorphism facilitates both (1) the definition of important notions for Heavyweight Ontology Engineering such as Compatible/Incompatible Axioms or Specialisation/Generalisation of Axioms and (2) the topological comparison of axioms, which in our work is used to define a new approach of ontology matching mainly based on axiom-based ontology morphisms.


Heavyweight Ontology Axioms Graph-Based Techniques Ontology Matching Ontology Evaluation Conceptual Graphs 


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    Fürst, F.: TooCoM: a Tool to Operationalize an Ontology with the Conceptual Graph Model. In: Proceedings of the Workshop on Evaluation of Ontology-Based Tools (EON 2003) at ISWC 2003, pp. 57–70 (2003)Google Scholar
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    Fúrst, F., Leclère, M., Trichet, F.: Operationalizing domain ontologies: a method and a tool. In: de Mantaras, R.L., Saitta, L. (eds.) European Conference on Artificial Intelligence (ECAI 2004), pp. 318–322. IOS Press, Amsterdam (2004)Google Scholar
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    Fürst, F., Trichet, F.: Axiom-based ontology matching. In: Proceedings of 3rd International Conference on Knowledge Capture (K-CAP 2005), Banff-Canada, pp. 195–196. ACM Press, New York (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Frédéric Fürst
    • 1
  • Francky Trichet
    • 2
  1. 1.LARIA – Laboratoire de Recherche en Informatique d’Amiens, CNRS-FRE 2733University of AmiensAmiens Cedex 01France
  2. 2.LINA – Laboratoire d’Informatique de Nantes Atlantique, CNRS-FRE 2729University of NantesNantes Cedex 03France

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