Applications of a categorical framework for conceptual data modeling
type: Item
instance of: scholarly article
title: Applications of a categorical framework for conceptual data modeling
zbMATH Open document ID: 0898.68024
author: Arthur H. M. ter Hofstede
author: E. Lippe
author: Theo P. van der Weide
published in: Acta Informatica
publication date: 1998-08-10T00:00:00Z
review text: For successful information systems development, conceptual data modeling is essential. Nowadays a plethora of techniques for conceptual data modeling exist. Many of these techniques lack a formal foundation and a lot of theory, e.g. concerning updates or schema transformations, is highly data model specific. As such there is a need for a unifying formal framework providing a sufficiently high level of abstraction. In this paper, focus is on the applications of such a framework defined in category theory. Well-known conceptual data modeling concepts, such as relationship types, generalization, specialization, and collection types are defined from a categorical point of view in this framework and an essential advantage is its ``configurable semantics''. Features such as null values, uncertainty, and temporal behavior can be added by selecting appropriate instance categories. The addition of these features usually requires a complete redesign of the formalization in traditional set-based approaches to semantics. Applications of the framework in the context of schema transformations and improved automated modeling support are discussed.
Mathematics Subject Classification ID: 68P99
Mathematics Subject Classification ID: 68P05
zbMATH DE Number: 1154580
zbMATH Keywords: conceptual data modeling
zbMATH Keywords: schema transformations
zbMATH Keywords: automated modeling support
MaRDI profile type: Publication
full work available at URL: s002360050112
OpenAlex ID: W2165420567
DOI: 10.1007/S002360050112
description: scientific article; zbMATH DE number 1154580