Data modelling versus ontology engineering

By Peter Spyns, R. Meersman, Mustafa Jarrar. SGMD, 2002

441 citations recorded by the source corpus.

Ontologies in current computer science parlance are computer based resources that represent agreed domain semantics. Unlike data models, the fundamental asset of ontologies is their relative independence of particular applications, i.e. an ontology consists of relatively generic knowledge that can be reused by different kinds of applications/tasks. The first part of this paper concerns some aspects that help to understand the differences and similarities between ontologies and data models. In the second part we present an ontology engineering framework that supports and favours the genericity of an ontology. We introduce the DOGMA ontology engineering approach that separates "atomic" conceptual relations from "predicative" domain rules. A DOGMA ontology consists of an ontology base that holds sets of intuitive context-specific conceptual relations and a layer of "relatively generic" ontological commitments that hold the domain rules. This constitutes what we shall call the double articulation of a DOGMA ontology 1.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/221da285b72f6272c2d7332a547d1e034a60e154

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jakob Beetz
2. Jos van Leeuwen
3. B. Vries

In Computer Networks and Communications

1. Jakob Beetz
2. Jos van Leeuwen
3. B. Vries

In Information Systems

1. Jakob Beetz
2. Jos van Leeuwen
3. B. Vries
4. Stefan Fenz
5. Andreas Ekelhart

Citations in the corpus

• IfcOWL: A case of transforming EXPRESS schemas into ontologies (2008, methodology): “Following the notion of “genericity” by Spyns et al. (2002), the general nature of the concepts defined in the IFCs already exhibit some basic requirements for the design of an ontology beyond a mere single purpose data model in that they are intended as a reusable, reliable (Uschold & King, 1995),…”
• Relationships and data sanitization: a study in scarlet (2010, background): “Sev­eral ontology languages such as DOGMA [82], Gellish [88], and IDEF5 [1] are highly domain speci.c; others such as CycL [76] use tools with unavailable source code, or that are proprietary.”