This is an interesting discussion. By coincidence, yesterday Tom
Briggs [1] defended his dissertation [2] on 'Constraint Generation and
Reasoning in OWL' which was done with Professor Yun Peng [3]. He
started with an analysis of Swoogle's data that showed that 75% of
published Semantic Web properties have neither domain or range
constraints and evaluated algorithms for inferring them. Rather than
focusing on instance data, he looked at what could be learned from how
the properties were used in the TBOX, e.g., for specifying role
restrictions. He has a paper on this that he has submitted to a
conference and should finish revising his dissertation in the next few
weeks. Here is the abstract for his defense:
Constraint Generation and Reasoning in OWL
Thomas H. Briggs
The majority of OWL ontologies in the emerging Semantic Web are
constructed from properties that lack domain and range
constraints. Constraints in OWL are different from the familiar uses
in programming languages and databases, and are actually type
assertions that are made about the individuals which are connected
by the property. These assertions can add vital information to the
model because they are assertions of type on the individuals
involved, and they can also give information on how the defining
property may be used.
Three different automated generation techniques are explored in this
research: disjunction, least-common named subsumer, and
vivification. Each algorithm is compared for the ability to
generalize, and the performance impacts with respect to the
reasoner. A large sample of ontologies from the Swoogle repository
are used to compare real-world performance of these techniques.
Finally, using generated facts, a type of default reasoning, may
conflict with future assertions to the knowledge base. While general
default reasoning is non-monotonic and undecidable a novel approach
is introduced to support efficient retraction of the default
knowledge. Combined, these techniques enable a robust and efficient
generation of domain and range constraints which will result in
inference of additional facts and improved performance for a number
of Semantic Web applications.
[1] http://ebiquity.umbc.edu/person/html/Tom/Briggs/
[2] http://ebiquity.umbc.edu/event/html/id/273/
[3] http://ebiquity.umbc.edu/person/html/Yun/Peng/
--
Tim Finin, Computer Science & Electrical Engineering, Univ of Maryland
Baltimore County, 1000 Hilltop Cir, Baltimore MD 21250. [EMAIL PROTECTED]
http://umbc.edu/~finin 410-455-3522 fax:-3969 http://ebiquity.umbc.edu
