Engineering Conceptual Data Models from Domain Ontologies: A Critical Evaluation

Engineering Conceptual Data Models from Domain Ontologies: A Critical Evaluation

Haya El-Ghalayini (University of the West of England (UWE), UK), Mohammed Odeh (University of the West of England (UWE), UK) and Richard McClatchey (University of the West of England (UWE), UK)
DOI: 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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Ontology Vs. Conceptual Data Model

This section informally explores ontologies and CDMs, including their similarities and differences. The literature shows many definitions of ontologies with the most popular definition proposed by Gruber (1995) as “a formal, explicit specification of a shared conceptualization” (p. 907). In general terms, an ontology may be defined as expressing knowledge in a machine-readable form to permit a common understanding of domain knowledge, so knowledge can be exchanged between heterogeneous environments.

On the other hand, conceptual data models capture the meaning of information for modelling an application and offer means for organizing information for the purposes of understanding and communication(Mylopoulos, 1998). The major role of the CDM is to model the so-called universe of discourse (UoD), entities and relationships in relation to particular user requirements independent of implementation issues. Hirschheim, Klein, and Lyytinen (1995) define the Universe of Discourse in the information systems (IS) world as “the slice of reality to be modelled” (p. 58). Therefore, there are some similarities and differences between ontologies and CDMs. Both are represented by a modeling grammar with similar constructs, such as classes in ontologies that correspond to entity types in CDMs. Thus, the methodologies of developing both models have common activities (Fonseca & Martin, 2005). While ontologies and CDMs share common features, they have some differences. According to Guarino’s (1998) proposal of ontology-driven information systems, an ontology can be used at the development or run time of IS, whereas a CDM is a building block of the analysis and design process of an IS.

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