Authors: Daniel L. Moody, Graeme G. Shanks
Tags: 1994, conceptual modeling
This paper develops a framework for evaluating the quality of data models and choosing between alternative representations of requirements. For any particular set of user requirements there are many possible models, each of which has drastically different implications for database and systems design. In the absence of formally defined and agreed criteria, the choice of an appropriate representation is usually made in an ad hoc way, based on personal opinion. The evaluation framework proposed consists of four major constructs: qualities (desirable properties of a data model), metrics (ways of measuring each quality), weightings (relative importance of each quality) and strategies (ways of improving data models). Using this framework, any two data models may be compared in an objective and comprehensive manner. The evaluation framework also builds commitment to the model by involving all stakeholders in the process: end users, management, the data administrator and application developers.Read the full paper here: https://link.springer.com/chapter/10.1007/3-540-58786-1_75
