Formal semantics-preserving translation from fuzzy ER model to fuzzy OWL DL ontology

  • Authors:

  • Z. M. Ma;Fu Zhang;Li Yan;Yanhui Lv

  • Affiliations:

  • (Correspd. E-mail: mazongmin@ise.neu.edu.cn) College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China;College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China;School of Software, Northeastern University, Shenyang, 110819, China;College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China

  • Venue:
  • Web Intelligence and Agent Systems
  • Year:
  • 2010

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Abstract

Ontology is an important part of the W3C standards for the Semantic Web, and how to quickly and cheaply construct Web ontologies has become a key technology to enable the Semantic Web. However, information imprecision and uncertainty exist in many real-world applications, thus constructing fuzzy ontology by extracting domain knowledge from fuzzy database models (e.g., fuzzy ER model) can profitably support fuzzy ontology development. In this paper, we propose an approach for constructing fuzzy ontology from fuzzy ER model, in which the fuzzy ontology consists of fuzzy ontology structure and instances. Firstly, we give the formal definition and the semantics of fuzzy ER models. Then, we introduce the fuzzy extension of ontology language OWL DL, i.e., fuzzy OWL DL. Based on the fuzzy OWL DL, a kind of fuzzy ontology called fuzzy OWL DL ontology is presented. Furthermore, we consider the fuzzy ER schema and the corresponding database instances, and translate them into the fuzzy ontology structure and the fuzzy ontology instances, respectively. Finally, since a fuzzy OWL DL ontology is equivalent to a fuzzy Description Logic f-SHOIN(D) knowledge base, how the reasoning problems of fuzzy ER models (e.g., satisfiability, subsumption, and redundancy) may be reduced to reasoning on f-SHOIN(D) knowledge bases is investigated, which will further contribute to constructing fuzzy OWL DL ontology that exactly meet application's needs. Of course, the correctness of the translation and reasoning problems are proved completely.