This paper describes the results of a 5-year research programme into evaluating and improving the quality of data models. A combination of field and laboratory research methods (action research, laboratory experiments and systems development) was used to empirically validate the framework. This paper describes how the framework was used to; quality assure a data model in a large application development project (product quality); reengineer application development processes to build quality into the data analysis process (process quality); investigate differences between data models produced by experts and novices; provide automated support for the evaluation process (the Data Model Quality Advisor). The results of the research have been used to refine and extend the framework, to the point that it is now a stable and mature approach.
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