Towards Semantically Grounded Decision Rules Using ORM + 

  • Yan Tang
  • Peter Spyns
  • Robert Meersman
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4824)


Recently, ontologies are proposed for many purposes to assist decision making, such as representing terminology and categorizing information. Current ontology-based decision support systems mainly contain semantically rich decision rules. In order to ground the semantics, we formalize those rules by committing them to domain ontologies. Those semantically grounded decision rules can represent the semantics precisely, thus improve the functionalities of many available rule engines. We model and visualize the rules by means of a novel extension of ORM. These rules are further stored in an XML-based markup language, ORM +  ML, which is a hybrid language of Rule-ML and ORM-ML. We demonstrate in the field of on-line customer management.


semantics ontologies DOGMA ORM markup language 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Yan Tang
    • 1
  • Peter Spyns
    • 1
  • Robert Meersman
    • 1
  1. 1.Semantics Technology and Applications Research Laboratory, Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 BRUSSEL 5Belgium

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