The quantity of biomedical information that’s posted on the internet grows daily. This abundant source is utilized to locate answers to problems across the life sciences. The Semantic Web for life sciences demonstrates assurance for correctly and effectively locating, integrating, querying and inferring relevant info which is required in daily biomedical research. Among the main technologies in the Semantic Web is ontologies, that furnish the semantics of the Semantic Web. Quite a few biomedical ontologies are already developed. A number of these ontologies consist of overlapping info, but it’s not likely that gradually you will see a single set of standard ontologies to which everybody will conform. As a result, applications frequently have to cope with multiple overlapping ontologies, however the heterogeneity of ontologies hampers interoperability among diverse ontologies. Aligning ontologies, i.e. identifying relationships between different ontologies, aims to get over this challenge.
Several ontology alignment systems are already developed. In these systems numerous methods and ideas have been suggested to help detection of alignments between ontologies. Nevertheless, there still is an array of problems to be resolved when we have alignment problems at hand. The task in this dissertation leads to three different facets of identification of high quality alignments: 1) Ontology alignment techniques and systems. We surveyed the prevailing ontology alignment systems, and suggested a standard ontology alignment framework. The majority of current systems can be viewed as instantiations of the framework. Also, we created a system for aligning biomedical ontologies (SAMBO) based on this framework. We applied several alignment strategies in the system. 2) Assessment of ontology alignment strategies. We produced and implemented the KitAMO framework for comparative evaluation of countless alignment strategies, and we examined various alignment strategies using the implementation. 3) Suggesting optimal alignment techniques for different applications. We recommended an approach to make recommendations.
Aligning Biomedical Ontologies Downloads
Source: Linköping University
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