Quality Of Data Models

Abstract

After a short overview of the definitions of the terms data model and quality three different approaches to quality of data models are described. The approaches have in common that neither application fields nor the users of data models are taken into account. The term quality is interpreted in a productionoriented way. The results of an empirical analysis conducted by the author are presented. They show that application fields and users differ widely in the various data models in different enterprises. The analysis concentrates on the missing aspects of the quality concepts in the literature: application fields, users, organizational context. A quality concept for data models which was developed by the author and is based on the results of the empirical analysis is outlined. The quality concept can be divided into two parts: a set of quality metrics and the description of a review process. Both parts are needed to evaluate data models effectively.