By Topic

Traditional, semantic, and hypersemantic approaches to data modeling

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Potter, W.D. ; Georgia Univ., Athens, GA, USA ; Trueblood, R.P.

An overview is given of past present data-modeling trends, and future directions are identified. The three traditional and commonly used data models that gained wide acceptance in the late 1960s and early 1970s and are used extensively today, namely the relational, hierarchical, and network models, are reviewed. Semantic data models that attempt to enhance the representation of operational information by capturing more of the meaning about data values and relationships are described. Enhancements to semantic data models that characterize hypersemantic data models and emphasize capturing inferential relationships are discussed.<>

Published in:

Computer  (Volume:21 ,  Issue: 6 )