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SAMBO -€“ A System for Aligning and Merging Biomedical Ontologies
Linköping University, Department of Computer and Information Science, IISLAB - Laboratory for Intelligent Information Systems.
Linköping University, Department of Computer and Information Science, IISLAB - Laboratory for Intelligent Information Systems.
2006 (English)In: Journal of Web Semantics, ISSN 1570-8268, Vol. 4, no 3, 196-206 p.Article in journal (Refereed) Published
Abstract [en]

Due to the recent explosion of the amount of on-line accessible biomedical data and tools, finding and retrieving the relevant information is not an easy task. The vision of a Semantic Web for life sciences alleviates these difficulties. A key technology for the Semantic Web is ontologies. In recent years many biomedical ontologies have been developed and many of these ontologies contain overlapping information. To be able to use multiple ontologies they have to be aligned or merged. In this paper we propose a framework for aligning and merging ontologies. Further, we developed a system for aligning and merging biomedical ontologies (SAMBO) based on this framework. The framework is also a first step towards a general framework that can be used for comparative evaluations of alignment strategies and their combinations. In this paper we evaluated different strategies and their combinations in terms of quality and processing time and compared SAMBO with two other systems.

Place, publisher, year, edition, pages
2006. Vol. 4, no 3, 196-206 p.
Keyword [en]
Ontologies; Alignment; Merging; Biomedical informatics, TECHNOLOGY, TEKNIKVETENSKAP
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hj:diva-18791DOI: 10.1016/j.websem.2006.05.003OAI: oai:DiVA.org:hj-18791DiVA: diva2:542158
Available from: 2012-07-30 Created: 2012-06-27 Last updated: 2012-11-30Bibliographically approved
In thesis
1. Aligning and Merging Biomedical Ontologies
Open this publication in new window or tab >>Aligning and Merging Biomedical Ontologies
2006 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Due to the explosion of the amount of biomedical data, knowledge and tools that are often publicly available over the Web, a number of difficulties are experienced by biomedical researchers. For instance, it is difficult to find, retrieve and integrate information that is relevant to their research tasks. Ontologies and the vision of a Semantic Web for life sciences alleviate these difficulties. In recent years many biomedical ontologies have been developed and many of these ontologies contain overlapping information. To be able to use multiple ontologies they have to be aligned or merged. A number of systems have been developed for aligning and merging ontologies and various alignment strategies are used in these systems. However, there are no general methods to support building such tools, and there exist very few evaluations of these strategies. In this thesis we give an overview of the existing systems. We propose a general framework for aligning and merging ontologies. Most existing systems can be seen as instantiations of this framework. Further, we develop SAMBO (System for Aligning and Merging Biomedical Ontologies) according to this framework. We implement different alignment strategies and their combinations, and evaluate them in terms of quality and processing time within SAMBO. We also compare SAMBO with two other systems. The work in this thesis is a first step towards a general framework that can be used for comparative evaluations of alignment strategies and their combinations.

Place, publisher, year, edition, pages
Linköping: Institutionen för datavetenskap, 2006. 14 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1225
Keyword
Ontologies, Ontology engineering, Biomedical ontologies, Ontology alignment, Ontology merging, Information technology
National Category
Computer and Information Science
Identifiers
urn:nbn:se:hj:diva-18793 (URN)
Opponent
Supervisors
Available from: 2012-11-30 Created: 2012-06-27 Last updated: 2012-11-30Bibliographically approved
2. Aligning Biomedical Ontologies
Open this publication in new window or tab >>Aligning Biomedical Ontologies
2007 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

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.

Place, publisher, year, edition, pages
Linköping: Institutionen för datavetenskap, 2007. 24 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1110
Keyword
ontologies, biomedical ontologies, aligning ontologies, semantic web, knowledge management, Computer science
National Category
Computer Science
Identifiers
urn:nbn:se:hj:diva-18787 (URN)978-91-85831-56-2 (ISBN)
Supervisors
Note

Teknologie doktorsexamen

Available from: 2012-11-30 Created: 2012-06-27 Last updated: 2012-11-30Bibliographically approved

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