vaida-abstract

Abstract - Ph D thesis He Tan

Aligning Biomedical Ontologies

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The amount of biomedical information that is disseminated over the Web
increases every day. This rich resource is used to find solutions to
challenges across the life sciences. The Semantic Web for life sciences
shows promise for effectively and efficiently locating, integrating,
querying and inferring related information that is needed in daily
biomedical research. One of the key technologies in the Semantic Web is
ontologies, which furnish the semantics of the Semantic Web. A large number
of biomedical ontologies have been developed. Many of these ontologies
contain overlapping information, but it is unlikely that eventually there
will be one single set of standard ontologies to which everyone will
conform. Therefore, applications often need to deal with multiple
overlapping ontologies, but the heterogeneity of ontologies hampers
interoperability between different ontologies.  Aligning ontologies, i.e.
identifying relationships between different ontologies, aims to overcome
this problem.

A number of ontology alignment systems have been developed. In these systems
various techniques and ideas have been proposed to facilitate identification
of alignments between ontologies. However, there still is a range of issues
to be addressed when we have alignment problems at hand. The work in this
thesis contributes to three different aspects of identification of high
quality alignments: 1) Ontology alignment strategies and systems. We
surveyed the existing ontology alignment systems, and proposed a general
ontology alignment framework. Most existing systems can be seen as
instantiations of the framework. Also, we developed a system for aligning
biomedical ontologies (SAMBO) according to this framework. We implemented
various alignment strategies in the system.  2) Evaluation of ontology
alignment strategies. We developed and implemented the KitAMO framework for
comparative evaluation of different alignment strategies, and we evaluated
different alignment strategies using the implementation. 3) Recommending
optimal alignment strategies for different applications. We proposed a
method for making recommendations.

short-ann

 

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Last modified on August 2007 by Anne Moe