DOGMA (Developing Ontology-Grounded Methods and Applications), which is a methodological framework for ontology engineering, was brought forward by Prof. Dr. R. Meersman (1999) and became mature in (Spyns et al., 2002, Jarrar and Meersman, 2007). It has its roots in database semantics and model theory. In DOGMA, an ontology is modeled by the double articulation principle into two layers: the lexon base layer and the commitment layer. A lexon is a plausible binary fact. The lexon base of an ontology describes a universe of discourse (UoD). Lexons are a more formal but still linguistically determined representation of propositions about a domain to be modeled (Spyns et al., 2007). A lexon contains five elements: context identifier, two terms and two roles.
Published in Chapter:
SDRule Markup Language: Towards Modeling and Interchanging Ontological Commitments for Semantic Decision Making
Yan Tang (Free University of Brussels, Belgium) and Robert Meersman (Free University of Brussels, Belgium)
Copyright: © 2009
|Pages: 25
DOI: 10.4018/978-1-60566-402-6.ch005
Abstract
The emergence of ontology based applications, e.g. the Semantic Web, marks the importance of ontologies. Application rules, such as decision making rules, are often committed to an existing domain ontology when a new application needs to be designed and developed. During this process, the semantics of application rules is required to be precisely grounded. In this chapter, we tackle the problems of modeling and interchanging ontological commitments in order to support ontology based decision making. We model and visualize ontological commitments by means of an extension to Object Role Modeling Language (ORM), which was called ORM Plus (ORM+) and is now named Semantic Decision Rule Language (SDRule-L). SDRule-L is a commitment language for modeling dynamic and non-monotonic decision rules. SDRule-L models are further stored in an XML-based markup language called Semantic Rule Markup Language (SDRule ML), which is a hybrid language of Rule Markup Language (Rule-ML) and Object Role Modeling Markup Language (ORM-ML). We also illustrate its supporting tool called SDRule-Lex, which is based on Tiny Lexon Browser (T-Lex). We demonstrate in the field of on-line customer management.