Authors: Geert Poels, Marcela Genero, Mario Piattini
Tags: 2007, conceptual modeling
Database and data model evolution cause significant problems in the highly dynamic business environment that weexperience these days. To support the rapidly changing data requirements of agile companies, conceptual data models,which constitute the foundation of database design, should be sufficiently flexible to be able to incorporate changes easilyand smoothly. In order to understand what factors drive the maintainability of conceptual data models and to improveconceptual modelling processes, we need to be able to assess conceptual data model properties and qualities in an objectiveand cost-efficient manner. The scarcity of early available and thoroughly validated maintainability measurement instru-ments motivated us to define a set of metrics for Entity–Relationship (ER) diagrams. In this paper we show that theseeasily calculated and objective metrics, measuring structural properties of ER diagrams, can be used as indicators ofthe understandability of the diagrams. Understandability is a key factor in determining maintainability as model modifi-cations must be preceded by a thorough understanding of the model. The validation of the metrics as early understand-ability indicators opens up the way for an in-depth study of how structural properties determine conceptual data modelunderstandability. It also allows building maintenance-related prediction models that can be used in conceptual data mod-elling practice.Read the full paper here: https://reader.elsevier.com/reader/sd/pii/S0169023X07001796?token=882C3548ADADE7989E884C378B319507A162C70A9187C63E212A7B5E8ABA7BC694E79102510F359AA796C9CADE7D1A15
