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.
Keywords
Rotation formalisms in three dimensionsComputer scienceRepresentation (politics)IDEF1XSemantic data modelData modelingData model (GIS)Data miningInformation retrievalObject (grammar)Theoretical computer scienceSoftware engineeringArtificial intelligenceSemantic WebMathematics
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Publication Info
- Year
- 1995
- Type
- article
- Volume
- 38
- Issue
- 6
- Pages
- 103-115
- Citations
- 113
- Access
- Closed
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Cite This
Young‐Gul Kim,
Salvatore T. March
(1995).
Comparing data modeling formalisms.
Communications of the ACM
, 38
(6)
, 103-115.
https://doi.org/10.1145/203241.203265
Identifiers
- DOI
- 10.1145/203241.203265