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An Evaluation of Description Logic for the Development of Product Models

Published

Author(s)

Xenia Fiorentini, Sudarsan Rachuri, Hyo Won Suh, Jae H. Lee, Ram D. Sriram

Abstract

The languages and logical formalisms developed by information scientists and logicians concentrate on the theory of languages and logical theorem proving. These languages, when used by domain experts to represent their domain of discourse, most often have issues related to the level of expressiveness and need specific extensions. In this paper we first analyze the requirements for the development of structured knowledge representation models for manufacturing products using ontologies. We then explore how these requirements can be satisfied through the levels of logical formalisms and expressivity of a structured knowledge representation model. We report our evaluation of Description Logic (DL) with respect to the requirements by giving an example of a product ontology developed with OWL (Ontology Web Language-Description Logic). In order to represent a product, we also need to combine both DL expressivity and domain-specific rules. Domain-specific rules are defined to add specific constraints in the knowledge base and we have used SWRL (Semantic Web Rule Language) for this purpose. We present a case study of an electro-mechanical product to validate the evaluation and further show how the OWL-DL reasoner together with the rule engine can enable reasoning of the product ontology. We finally discuss the open issues such as capabilities and limitations related to the usage of DL, OWL and SWRL for product modeling.
Citation
Journal of Computing and Information Science in Engineering

Keywords

description logic, product models, ontology, DL, OWL, Ontology Web Language-Description Logic, SWRL, Semantic Web Rule Language, manufacturing

Citation

Fiorentini, X. , Rachuri, S. , , H. , Lee, J. and Sriram, R. (2008), An Evaluation of Description Logic for the Development of Product Models, Journal of Computing and Information Science in Engineering, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=900220 (Accessed December 12, 2024)

Issues

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Created November 10, 2008, Updated February 19, 2017