Data modelling versus ontology engineering

Abstract

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 .

Ontology-based standards development: Application of OntoStanD to ebXML business process specification schema

“…'Knowledge Breakdown' in OntoStanD is followed by 'Knowledge Elicitation' which is concerned with the conceptual modeling of a standard and leads to the development of the baseline taxonomy of the terms used in a standard and later the ontology base layer, according to the definition provided by Spyns et al (2002), which represents the domain terms and their relationships as explained below.…”

A Holistic Approach for the Architecture and Design of an Ontology-Based Data Integration Capability in Product Master Data Management

“…[13] Distinguishes ontology engineering from conventional data modeling. Ontology engineering covers a domain wide semantics and relationships within.…”

DOGMA-MESS: A Meaning Evolution Support System for Interorganizational Ontology Engineering

“…The DOGMA (Designing Ontology-Grounded Methods and Applications) approach to ontology engineering, developed at VUB STARLab, aims to satisfy real-world needs by developing a useful and scalable ontology engineering approach [17]. Its philosophy is based on a double articulation: an ontology consists of an ontology base of lexons, which holds (multiple) intuitive conceptualizations of a domain, and a layer of reified ontological commitments.…”