To read the full version of this content please select one of the options below:

NaLER: a natural language method for interpreting entity‐relationship models

Clare Atkins (Clare Atkins is a Lecturer at Massey University, Palmerston North, New Zealand.)
Jon Patrick (Jon Patrick is a Professor at Basser Department of Computer Science, University of Sydney, Australia.)

Campus-Wide Information Systems

ISSN: 1065-0741

Article publication date: 1 August 2000

Abstract

Entity‐relationship (E‐R) models continue to be the most common means of documenting the data requirements of information systems. Whether used as the basis for relational database design or to record organisational conceptual data structures, it is essential that the information content (the semantics) of such models is clearly understood by both the builders and the users of such models. In particular, novice data modellers, or users, and their teachers need to understand how well a model represents a particular scenario description. Presents a practical method that has been developed for use by data modelling students. This method, termed NaLER (Natural Language for E‐R), provides student data modellers with a more organised way of assessing the information content of models that they or others have produced. It can also be used as a means of comparing those models with the information contained within the original description of the Universe of Discourse (UoD). It is suggested that the method could be of practical benefit not only to students but also to anyone with a need to ascertain the semantic content of a data model.

Keywords

Citation

Atkins, C. and Patrick, J. (2000), "NaLER: a natural language method for interpreting entity‐relationship models", Campus-Wide Information Systems, Vol. 17 No. 3, pp. 85-93. https://doi.org/10.1108/10650740010326627

Publisher

:

MCB UP Ltd

Copyright © 2000, MCB UP Limited