Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10321255 | Data & Knowledge Engineering | 2005 | 34 Pages |
Abstract
An international standard has now been established for evaluating the quality of software products. However there is no equivalent standard for evaluating the quality of conceptual models. While a range of quality frameworks have been proposed in the literature, none of these have been widely accepted in practice and none has emerged as a potential standard. As a result, conceptual models continue to be evaluated in practice in an ad hoc way, based on common sense, subjective opinions and experience. For conceptual modelling to progress from an “art” to an engineering discipline, quality standards need to be defined, agreed and applied in practice. This paper conducts a review of research in conceptual model quality and identifies the major theoretical and practical issues which need to be addressed. We consider how conceptual model quality frameworks can be structured, how they can be developed, how they can be empirically validated and how to achieve acceptance in practice. We argue that the current proliferation of quality frameworks is counterproductive to the progress of the field, and that researchers and practitioners should work together to establish a common standard (or standards) for conceptual model quality. Finally, we describe some initial efforts towards developing a common standard for data model quality, which may provide a model for future standardisation efforts.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Daniel L. Moody,