AIC Seminar Series
Combining Ontologies and Rules: 2 Example Approaches
Notice: Hosted by Vinay Chaudhri.
Date: 2011-08-22 at 10:00
Location: EJ228 (SRI E building) (Directions)
The problem of combining ontologies (in the form of Description Logics
knowledge bases) with rules (in the form of Logic Programming rules)
evolves around 2 distinct approaches: a tightly-integrated approach
and a loosely-coupled approach. In the presentation, we will define
the distinguishing features of those approaches.
In particular, we will pick an exemplary framework from each approach:
Open Answer Set Programming as an implementation vehicle for
tightly-coupled approaches and DL-programs as an example of a
loosely-coupled approach. We will define these 2 frameworks and
analyze some of its key properties, including expressiveness and
complexity. Furthermore, we will indicate what the state-of-the-art
with respect to these approaches is and what the possible directions
for future work are.
Dr. Heymans obtained in 2006 a PhD in Theoretical Computer Science
from the Free University of Brussels, Belgium, on the integration of
ontologies and rules. From 2006 to 2008, he was a PostDoc researcher
at the Digital Enterprise Research Institute, Austria. In Innsbruck,
he led a research team of researchers in several European Union
projects. He was a work package leader in the SUPER project on using
semantics for business processes. In 2008-2011, he was the Principal
Investigator for an Austrian research project (``Distributed Open
Answer Set Programming’’) as well as the local project manager for the
EU project OntoRule at the Vienna University of Technology with the
group of Prof. Thomas Eiter. Currently, he is a Semantic Architect at
SemanticBits LLC, United States, a company specialized in health care
solutions. Dr. Heymans authored 53 publications (his h-index is 15),
organized 4 workshops, and was in the Program Committee of 27
international workshops and conferences. His specialty is in
Artificial Intelligence and Semantic Technologies research, in
particular Knowledge Representation and Reasoning using formal
languages such as Description Logics and Logic Programming.
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