Speaker: Kathryn Blackmond Laskey, George Mason University

Title: Probabilistic Ontologies for High-Level Fusion in a Net-Centric Environment

Extended abstract

Brief abstract:

Advances in bandwidth and processing power, together with maturing technology for low-level fusion, have created both the need and the opportunity for the emergence of new approaches to the problem of high-level fusion. Current
approaches to high-level fusion require cognitively burdensome manual processing. Because uncertainty is ubiquitous, support for uncertainty is essential to successful knowledge fusion. Traditional ontology formalisms lack inbuilt methods to
represent and process uncertainty. This paper describes a framework for representing domain semantics, including uncertainty, in a probabilistic ontology and reasoning with that knowledge to provide automated support for high-level fusion.

Bio sketch:
Kathryn Blackmond Laskey, Ph.D., is Associate Director of the Center of Excellence in Command, Control, Communications, Computing and Intelligence (C4I Center) and Associate Professor of Systems Engineering and Operations Research at George Mason University. She teaches and performs research on computational decision theory and evidential reasoning. Professor Laskey’s research is focused on methods for representing knowledge in forms that can be processed by computers, extending traditional knowledge representation methods to represent uncertainty, eliciting knowledge from human experts, applying probability theory to draw conclusions from evidence arising from multiple sources.  Dr. Laskey developed multi-entity Bayesian networks (MEBN), a language and logic that extends classical first-order logic to support Bayesian probability. She was a key contributor to the development of PR-OWL, an upper ontology that allows MEBN theories to be represented in OWL ontologies. As an invited expert to the World Wide Web Consortium (W3C), Dr. Laskey co-chaired the Uncertainty Reasoning for the World Wide Web Experimental Group (URW3-XG), a group devoted to identifying aspects of uncertainty that need to be standardized for web-based applications. Dr. Laskey received the BS degree in mathematics from the University of Pittsburgh, the MS degree in mathematics from the University of Michigan, and the PhD degree in statistics and public policy from Carnegie Mellon University.