NIST-Ontolog-NCOR Mini-Series: Ontology Measurement and Evaluation (Session-5) - Thu 29-Mar-2007    (UV9)

Conference Call Details    (VHV)

Attendees    (VIM)

Background    (VIY)

This is the 5th event of a mini-series of talks and discussions that revolve around the topic: "Ontology Measurement and Evaluation" during which this community will explore the landscape, issues and solutions relating to the measurement, evaluation, quality and testing of ontologies.    (VIZ)

This is a Joint NIST-Ontolog-NCOR initiative. A planning meeting for this mini-series took place on 22-Aug-2006, during which the scope and plans for the program was discussed among members of the community. Dr. Steven Ray, who is the Chief of NIST's Manufacturing Systems Integration Division (MSID), a long time member of the Ontolog community, as well as the convener of NCOR's Ontology Evaluation Committee, was invited to champion the program. This series is expected to last about 6 months during which invited speaker and technical discussion events will be featured (at the rate of about one event per month).    (VJ0)

See also: OntologyMeasurementEvaluation (the 'project' homepage for this mini-series)    (VJ1)

Agenda & Proceedings: "Ontology Measurement and Evaluation" - Mini-series Session-5    (VJ2)

Panel Discussion on: "Probabilistic Reasoning and Ontology Evaluation"    (VJ3)

Topic: "Probabilistic Reasoning and Ontology Evaluation"    (VJB)

by KenBaclawski, KathyLaskey, PauloCosta, TerryJanssen & SteveRay    (VJC)

The Semantic Web is an extension of the World Wide Web in which information is given a well-defined meaning, so that computers and people may more easily work in cooperation. This is done by introducing a framework in which one can represent formal logical statements and perform logical inference. However, the Semantic Web does not include a mechanism for empirical, scientific reasoning which is based on stochastic inference. The purpose of this session is to survey and evaluate proposed mechanisms for integrating probabilistic reasoning with logical reasoning in general, and with the Semantic Web in particular.    (UUY)

Some of the characteristics that distinguish the proposed mechanisms and languages include: expressiveness, modularity, support for continuous random variables, and compatibility with the Semantic Web. Probabilistic reasoning systems can be characterized by features such as: the language used to specify probabilistic knowledge, the expressiveness of the query language, the background probabilistic ontology used by the system, and the mechanism for integration with logical reasoning. This panel discussion will address these and other characteristics and discuss how they might be incorporated when evaluating probabilistic ontologies.    (UUZ)

Questions, Answers & Discourse:    (VJI)

Audio Recording of this Session    (VJS)