Welcome to the InfoSci Platform
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: © 2008 |Pages: 13
ISBN13: 9781599049519|ISBN10: 1599049511|EISBN13: 9781599049526
DOI: 10.4018/978-1-59904-951-9.ch060
Cite Chapter Cite Chapter

MLA

El-Ghalayini, Haya, et al. "Engineering Conceptual Data Models from Domain Ontologies: A Critical Evaluation." Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications, edited by John Wang, IGI Global, 2008, pp. 1068-1080. https://doi.org/10.4018/978-1-59904-951-9.ch060

APA

El-Ghalayini, H., Odeh, M., & McClatchey, R. (2008). Engineering Conceptual Data Models from Domain Ontologies: A Critical Evaluation. In J. Wang (Ed.), Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications (pp. 1068-1080). IGI Global. https://doi.org/10.4018/978-1-59904-951-9.ch060

Chicago

El-Ghalayini, Haya, Mohammed Odeh, and Richard McClatchey. "Engineering Conceptual Data Models from Domain Ontologies: A Critical Evaluation." In Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications, edited by John Wang, 1068-1080. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-951-9.ch060

Export Reference

Mendeley
Favorite

Abstract

This article 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 developing information systems. 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 article 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.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.