A unifying framework for conceptual data modelling concepts

For successful information systems development, conceptual data modelling is essential. Nowadays many techniques for conceptual data modelling exist: examples are NIAM, FORM, PSM, many (E)ER variants, IFO, and FDM. In-depth comparisons of concepts of these techniques are very difficult as the mathem...

Full description

Saved in:
Bibliographic Details
Published in:Information and software technology 1997, Vol.39 (1), p.15-25
Main Authors: Frederiks, P.J.M., ter Hofstede, A.H.M., Lippe, E.
Format: Article
Language:English
Subjects:
Category theory
Conceptual data modelling
Mathematical analysis
Mathematical models
Meta modelling
Methods
Software
Studies
Systems development
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:For successful information systems development, conceptual data modelling is essential. Nowadays many techniques for conceptual data modelling exist: examples are NIAM, FORM, PSM, many (E)ER variants, IFO, and FDM. In-depth comparisons of concepts of these techniques are very difficult as the mathematical formalizations of these techniques, if existing at all, are very different. As such there is a need for a unifying formal framework providing a sufficiently high level of abstraction. In this paper the use of category theory for this purpose is addressed. Well-known conceptual data modelling concepts are discussed from a category theoretic point of view. Advantages and disadvantages of the approach chosen will be outlined.
ISSN:0950-5849
1873-6025
DOI:10.1016/0950-5849(96)01112-3