ACM SIGMOD Anthology ACM SIGMOD dblp.uni-trier.de

Semantic Data Models.

Joan Peckham, Fred J. Maryanski: Semantic Data Models. ACM Comput. Surv. 20(3): 153-189(1988)
@article{DBLP:journals/csur/PeckhamM88,
  author    = {Joan Peckham and
               Fred J. Maryanski},
  title     = {Semantic Data Models},
  journal   = {ACM Comput. Surv.},
  volume    = {20},
  number    = {3},
  year      = {1988},
  pages     = {153-189},
  ee        = {db/journals/csur/PeckhamM88.html},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

Semantic data models have emerged from a requirement for more expressive conceptual data models. Current generation data models lack direct support for relationships, data abstraction, inheritance, constraints, unstructured objects, and the dynamic properties of an application. Although the need for data models with richer semantics is widely recognized, no single approach has won general acceptance. This paper describes the generic properties of semantic data models and presents a representative selection of models that have been proposed since the mid-1970s. In addition to explaining the features of the individual models, guidelines are offered for the comparison of models. The paper concludes with a discussion of future directions in the area of conceptual data modeling.

Copyright © 1988 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.


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