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GMU C4I Center Seminar

Co-sponsor: Department of Systems Engineering and Operations Research

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Bayesian Ontologies for Semantically Aware Systems

Dr. Kathryn Blackmond Laskey
Associate Director, C4I Center
Systems Engineering and Operations Research

Friday, April 28, 2006

ABSTRACT

Ontologies have become ubiquitous in current-generation information systems. An ontology is an explicit, formal representation of the entities and relationships that can exist in a domain of application. Following a well-trodden path, initial research in computational ontology has neglected uncertainty, developing almost exclusively within the framework of classical logic. As appreciation grows of the limitations of ontology formalisms that cannot represent uncertainty, the demand from user communities increases for ontology formalisms with the power to express uncertainty. Support for uncertainty is essential for interoperability, knowledge sharing, and knowledge reuse. Bayesian ontologies are used to describe knowledge about a domain with its associated uncertainty in a principled, structured, sharable, and machine-understandable way.

This paper considers Multi-Entity Bayesian Networks (MEBN) as a logical basis for Bayesian ontologies, and describes PR-OWL, a MEBN-based probabilistic extension to the ontology language OWL. A case study is presented in information security, to illustrate the role ontologies can play in developing and maintaining interoperable systems.