A fine-grained approach to resolving unsatisfiable ontologies

  • Authors:

  • Joey Sik Chun Lam;Derek Sleeman;Jeff Z. Pan;Wamberto Vasconcelos

  • Affiliations:

  • Department of Computing Science, University of Aberdeen, UK;Department of Computing Science, University of Aberdeen, UK;Department of Computing Science, University of Aberdeen, UK;Department of Computing Science, University of Aberdeen, UK

  • Venue:
  • Journal on data semantics X
  • Year:
  • 2008

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Abstract

The ability to deal with inconsistencies and to evaluate the impact of possible solutions for resolving inconsistencies are of the utmost importance in real world ontology applications. The common approaches either identify the minimally unsatisfiable sub-ontologies or the maximally satisfiable sub-ontologies. However there is little work which addresses the issue of rewriting the ontology; it is not clear which axioms or which parts of axioms should be repaired, nor how to repair those axioms. In this paper, we address these limitations by proposing an approach to resolving unsatisfiable ontologies which is fine-grained in the sense that it allows parts of axioms to be changed. We revise the axiom tracing technique first proposed by Baader and Hollunder, so as to track which parts of the problematic axioms cause the unsatisfiability. Moreover, we have developed a tool to support the ontology user in rewriting problematic axioms. In order to minimise the impact of changes and prevent unintended entailment loss, both harmful and helpful changes are identified and reported to the user. Finally we present an evaluation of our interactive debugging tool and demonstrate its applicability in practice.