Information systems (IS) are quickly emerging as critical resources to be leveraged for organizational productivity in many business, social, and economic enterprises. The explosive growth in information technology (IT) can be broadly attributed to the emerging novel linkages of IS/IT with several base disciplines, extending the reach of IS/IT to application domains never previously considered. […]
Salvatore T. March
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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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