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Engineering Conceptual Data Models from Domain Ontologies: A Critical Evaluation

Engineering Conceptual Data Models from Domain Ontologies: A Critical Evaluation

Haya El-Ghalayini, Mohammed Odeh, Richard McClatchey
Copyright: © 2009 |Pages: 13
ISBN13: 9781605664187|ISBN10: 1605664189|ISBN13 Softcover: 9781616925086|EISBN13: 9781605664194
DOI: 10.4018/978-1-60566-418-7.ch019
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MLA

El-Ghalayini, Haya, et al. "Engineering Conceptual Data Models from Domain Ontologies: A Critical Evaluation." Integrated Approaches in Information Technology and Web Engineering: Advancing Organizational Knowledge Sharing, edited by Ghazi I. Alkhatib and David C. Rine, IGI Global, 2009, pp. 304-316. https://doi.org/10.4018/978-1-60566-418-7.ch019

APA

El-Ghalayini, H., Odeh, M., & McClatchey, R. (2009). Engineering Conceptual Data Models from Domain Ontologies: A Critical Evaluation. In G. Alkhatib & D. Rine (Eds.), Integrated Approaches in Information Technology and Web Engineering: Advancing Organizational Knowledge Sharing (pp. 304-316). IGI Global. https://doi.org/10.4018/978-1-60566-418-7.ch019

Chicago

El-Ghalayini, Haya, Mohammed Odeh, and Richard McClatchey. "Engineering Conceptual Data Models from Domain Ontologies: A Critical Evaluation." In Integrated Approaches in Information Technology and Web Engineering: Advancing Organizational Knowledge Sharing, edited by Ghazi I. Alkhatib and David C. Rine, 304-316. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-418-7.ch019

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Abstract

This paper studies the differences and similarities between domain ontologies and conceptual data models and the role that ontologies can play in establishing conceptual data models during the process of information systems development. A mapping algorithm has been proposed and embedded in a special purpose Transformation Engine to generate a conceptual data model from a given domain ontology. Both quantitative and qualitative methods have been adopted to critically evaluate this new approach. In addition, this paper focuses on evaluating the quality of the generated conceptual data model elements using Bunge-Wand-Weber and OntoClean ontologies. The results of this evaluation indicate that the generated conceptual data model provides a high degree of accuracy in identifying the substantial domain entities along with their relationships being derived from the consensual semantics of domain knowledge. The results are encouraging and support the potential role that this approach can take part in the process of information system development.

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