Abstract
In an open, constantly changing and collaborative environment like the forthcoming Semantic Web, it is reasonable to expect that knowledge sources will contain noise and inaccuracies. Practical reasoning techniques for ontologies therefore will have to be tolerant to this kind of data, including the ability to handle inconsistencies in a meaningful way. For this purpose, we employ paraconsistent reasoning based on four-valued logic, which is a classical method for dealing with inconsistencies in knowledge bases. Its transfer to OWL DL, however, necessitates the making of fundamental design choices in dealing with class inclusion, which has resulted in differing proposals for paraconsistent description logics in the literature. In this paper, we build on one of the more general approaches which due to its flexibility appears to be most promising for further investigations. We present two algorithms suitable for implementation, one based on a preprocessing before invoking a classical OWL reasoner, the other based on a modification of the KAON2 transformation algorithms. We also report on our implementation, called ParOWL.
We acknowledge support by the German Federal Ministry of Education and Research (BMBF) under the SmartWeb project (grant 01 IMD01 B), by the EU under the IST project NeOn (IST-2006-027595, http://www.neon-project.org/), by the Deutsche Forschungsgemeinschaft (DFG) in the ReaSem project, and by China Scholarship Council, and partially by NSFC (grant numbers 60373002 and 60496322) and by NKBRPC (2004CB318000).
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Ma, Y., Hitzler, P., Lin, Z. (2007). Algorithms for Paraconsistent Reasoning with OWL. In: Franconi, E., Kifer, M., May, W. (eds) The Semantic Web: Research and Applications. ESWC 2007. Lecture Notes in Computer Science, vol 4519. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72667-8_29
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