DeLorean: A reasoner for fuzzy OWL 2

  • Authors:

  • Fernando Bobillo;Miguel Delgado;Juan Gómez-Romero

  • Affiliations:

  • Department of Computer Science and Systems Engineering, University of Zaragoza, Spain;Department of Computer Science and Artificial Intelligence, University of Granada, Spain;Applied Artificial Intelligence Group, University Carlos III, Madrid, Spain

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2012

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Abstract

Today, there is a growing interest in the development of knowledge representations able to deal with uncertainty, which is a very common requirement in real world applications. Despite the undisputed success of ontologies, classical ontologies are not suitable to deal with uncertainty and, consequently, several extensions with fuzzy logic and rough logic, among other formalisms, have been proposed. In this article we describe DeLorean 2, the first ontology reasoner that supports fuzzy extensions of the standard languages OWL and OWL 2. In a strict sense, DeLorean is not a reasoner but a translator from fuzzy rough ontology languages (GZSROIQ(D)) into classical ontology languages (SROIQ(D)). This allows using classical (widely available) Description Logic inference engines to reason with the representation resulting from the transformation. We describe the main features of the application: evolution, functionality, architecture, graphical interface, input language, and implementation details.