Comparing data modeling formalisms

Accurate specification and validation of information requirements is critical to the development of organizational information systems. Semantic data models were developed to provide a precise and unambiguous representation of organizational information requirements [9, 17]. They serve as a communication vehicle between analysts and users. After analyzing 11 semantic data models, Biller and Neuhold [3] conclude that there are essentially only two types of data modeling formalisms: entity-attribute-relationship (EAR) models and object-relationship (OR) models. Proponents of each claim their model yields “better” representations [7] than the other. There is, however, little empirical evidence to substantiate these claims.

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