1. Cross-Ontological Relationships
Good morning and thank you all for being here. I am a Ph.D. student at UCCS and a Principal Investigator at the MITRE Corporation. Today I will be sharing with you original research in the area of ontology mapping.
To describe this approach…
Acquiring Complex
Cross-Ontological Relationships
Justin Gray
28 January 2009

2. Introduction
An ontology is a partial, explicit, formal specification of a shared conceptualization
Standards for ontology representation such as the Web Ontology Language (OWL) has led to tremendous growth in ontologies exposed on the Web
Proliferation of knowledge sharing on the Web has resulted in a growing need for integration of knowledge
“As different parties generate ontologies independently, the level of heterogeneity across platforms increases” [Euzenat & Shvaiko 2007]
Ontology Mapping is a process of acquiring relationships between ontological entities

3. Gaps in Capability
Significant body of work in the area of schema matching and ontology alignment
50+ approaches published to date
None of the approaches exploit the characteristics of OWL in ontology matching [Euzenat et al. 2006]
None of the approaches exploit upper ontologies
Nearly all approaches seek to learn equivalence relations
Only a few acquire other relationships [Palopoli et al. 2003], [Kotis et al. 2006], [Kim et al. 2005]
Relationships restricted to hypernymy, hyponymy, inclusion, subsumption
Most approaches apply alignment for data integration, transformation and query answering
Very few focus on Web service composition [Hibner and Zielinski 2007] [Corcho et al. 2003] and mediation

4. Advance the state of the art in ontology alignment
Research Objectives
Contribute new evidence for ontology alignment: use of the semantics of OWL and upper ontologies
Contribute algorithms to acquire new information in ontology alignment: relationships beyond equivalence
Demonstrate new application of ontology alignment: Web service composition and mediation
To address these gaps in capability, we propose the following objectives.…..
Today, I will be primarily focused on describing the new evidence and algorithms……Use of ontology alignment for web service mediation is an enhancement we are exploring now…..
With these objectives in mind…
Advance the state of the art in ontology alignment

5. Relationships to Acquire
Hyponymy, or subclass relation
“Relations in R”, generic relations contained within the ontologies to align
Hypernymy, or superclass relation
Meronymy, to include partOf, hasPart
Disjointness, relation in which no instances are shared between classes
Note: I give the whole picture here, but verbally state that we just have results for the first 2 right now. I have since tested hypernymy and am now working on meronymy and disjointness. We are also well into testing using bio ontologies.

6. Evaluation
Ontologies chosen from web in domain of academic conferences, students, etc.
Reference alignment generated semi-automatically
Precision and recall measured against reference alignment
Ontology pairs selected to test as many pattern combinations as possible

7. Contribute to state of the art in ontology alignment
Summary and Next Steps
We propose to advance the state of the art in ontology mapping
Contribute new evidence, algorithms and applications
Semantics of OWL, WordNet and OpenCyc have been applied to acquire hyponymy and generic “Relations in R”
Preliminary results are promising in a simple domain
Next steps include:
Test ontology mapping in bioinformatics domain
Identify new relations to acquire and new types of evidence
Apply machine learning to the problem to optimize application of evidence
Apply alignment for web service composition and mediation
Contribute to state of the art in ontology alignment