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Automatic Construction of OWL Ontologies From Petri Nets

Author

Listed:
  • Zongmin Ma

    (Nanjing University of Aeronautics and Astronautics, Nanjing, China)

  • Haitao Cheng

    (Nanjing University of Posts and Telecommunications, Nanjing, China)

  • Li Yan

    (College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China)

Abstract

Ontology, as a formal representation method of domain knowledge, plays a particular important key role in semantic web. How to construct ontologies has become a key technology in the semantic web, especially constructing ontologies from existing domain knowledge. Currently, Petri nets have been a mathematical modeling tool, and have been widely studied and successfully applied in modeling of software engineering, database and artificial intelligence. In particular, PNML (Petri Net Markup Language) language has been a part of ISO/IEC Petri nets standard for representing and exchanging data on Petri nets. Therefore, how to construct ontologies from PNML model of Petri nets needs to be investigated. In this article, the authors investigate a method for automatic construction of web ontology language (OWL) ontologies from PNML of Petri nets. Firstly, this paper gives a formal definition and the semantics of PNML models of Petri nets. On this basis, a formal approach for constructing OWL ontologies from PNML model of Petri nets is proposed, i.e., this paper transforms Petri nets (including PNML model and PNML document of the Petri nets) into OWL ontologies at both structure and instance levels. Furthermore, the correctness of the transformation is proved. Finally, a prototype construction tool called PN2OWL is developed to transform Petri nets models into OWL ontologies automatically.

Suggested Citation

  • Zongmin Ma & Haitao Cheng & Li Yan, 2019. "Automatic Construction of OWL Ontologies From Petri Nets," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 15(1), pages 21-51, January.
    • Handle: RePEc:igg:jswis0:v:15:y:2019:i:1:p:21-51
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    Cited by:

    1. Hoxtell, Annette, 2020. "Automatisierung qualitativer Marktforschung mit Künstlicher Intelligenz," PraxisWISSEN Marketing: German Journal of Marketing, AfM – Arbeitsgemeinschaft für Marketing, vol. 5(01/2020), pages 111-123.
    2. Arulsamy, Karen & Delaney, Liam, 2022. "The impact of automatic enrolment on the mental health gap in pension participation: Evidence from the UK," Journal of Health Economics, Elsevier, vol. 86(C).
    3. Kendrik Yan Hong Lim & Pai Zheng & Chun-Hsien Chen, 2020. "A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1313-1337, August.

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