Comparing data modeling formalisms

  • Authors:
  • Young-Gul Kim;Salvatore T. March

  • Affiliations:
  • Department of MIS, KAist, P.O. Box 201, Cheong-Ryang, Seoul, 130-650, Korea;Information and Decision Science Department. C.L. Carlson School of Management, University of Minnesota, 271 19th Ave. S., Minneapolis, MN

  • Venue:
  • Communications of the ACM
  • Year:
  • 1995

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Abstract

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.