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Capturing, Representing and Operationalising Semantic Integration (CROSI) project - final report

Capturing, Representing and Operationalising Semantic Integration (CROSI) project - final report
Capturing, Representing and Operationalising Semantic Integration (CROSI) project - final report
In October of 2004, the University of Southampton and Hewlett Packard Laboratories at Bristol joined forces to work on a collaborated project, CROSI, in order to investigate semantic integration. The project lasted 12 months and its primary focus was the use of Artificial Intelligence technology, like ontologies, in the Semantic Web environment in order to research issues related to ontology mapping. A number of new insights and emergent issues were identified by using a practical testbed and a thorough evaluation strategy. The project's main deliverables were: (a) a comprehensive survey of state-of-the-art technologies that address semantic integration; (b) engineering artifacts for guiding the potential semantic integration practitioner to develop a semantic integration system: the Semantic Intensity Spectrum (SIS) and a Modular Architecture for developing semantic integration systems; (c) an ontology mapping prototype system, CMS (CROSI Mapping System) which acts as a demonstrator of mapping techniques. CROSI also shed light and provided fruitful insights for potential extensions of this technology. For example, it was proven that combining different matchers gives us a better alignment than using them independently. But, we also identified areas where more research is needed, like for example, practical and re-usable algorithms for aggregating alignment results. The project also had a good visibility record and achieved a decent dissemination across various communities (Web community, Knowledge Engineering community), especially when its short life cycle is taken into account. The highlight was our participation in the annual ontology alignment contest where CMS was ranked in the top three systems for alignment and it was one of the two out of seven participating systems that managed to parse correctly and without a flaw the industrial-strength, sizeable ontologies in the medical informatics domain. In this final project report, we elaborate on the issues mentioned above. This report is also accompanied by a software system and its manual where more technical details regarding the mechanisms used for alignment are explained.
s.n.
Kalfoglou, Yannis
d3d242fd-4ce2-4041-b8ea-aa3b3bec3b88
Hu, Bo
927680e6-b2b4-4b88-9a6e-20a86bb9d2d2
Reynolds, Dave
d9a2f295-e6a4-4ca9-ba47-ea97c32d44f2
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Kalfoglou, Yannis
d3d242fd-4ce2-4041-b8ea-aa3b3bec3b88
Hu, Bo
927680e6-b2b4-4b88-9a6e-20a86bb9d2d2
Reynolds, Dave
d9a2f295-e6a4-4ca9-ba47-ea97c32d44f2
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7

Kalfoglou, Yannis, Hu, Bo, Reynolds, Dave and Shadbolt, Nigel (2005) Capturing, Representing and Operationalising Semantic Integration (CROSI) project - final report s.n.

Record type: Monograph (Project Report)

Abstract

In October of 2004, the University of Southampton and Hewlett Packard Laboratories at Bristol joined forces to work on a collaborated project, CROSI, in order to investigate semantic integration. The project lasted 12 months and its primary focus was the use of Artificial Intelligence technology, like ontologies, in the Semantic Web environment in order to research issues related to ontology mapping. A number of new insights and emergent issues were identified by using a practical testbed and a thorough evaluation strategy. The project's main deliverables were: (a) a comprehensive survey of state-of-the-art technologies that address semantic integration; (b) engineering artifacts for guiding the potential semantic integration practitioner to develop a semantic integration system: the Semantic Intensity Spectrum (SIS) and a Modular Architecture for developing semantic integration systems; (c) an ontology mapping prototype system, CMS (CROSI Mapping System) which acts as a demonstrator of mapping techniques. CROSI also shed light and provided fruitful insights for potential extensions of this technology. For example, it was proven that combining different matchers gives us a better alignment than using them independently. But, we also identified areas where more research is needed, like for example, practical and re-usable algorithms for aggregating alignment results. The project also had a good visibility record and achieved a decent dissemination across various communities (Web community, Knowledge Engineering community), especially when its short life cycle is taken into account. The highlight was our participation in the annual ontology alignment contest where CMS was ranked in the top three systems for alignment and it was one of the two out of seven participating systems that managed to parse correctly and without a flaw the industrial-strength, sizeable ontologies in the medical informatics domain. In this final project report, we elaborate on the issues mentioned above. This report is also accompanied by a software system and its manual where more technical details regarding the mechanisms used for alignment are explained.

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Published date: October 2005
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 261717
URI: https://eprints.soton.ac.uk/id/eprint/261717
PURE UUID: 5e7072af-9019-45c9-968c-de6d3c0b1e65

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Date deposited: 21 Dec 2005
Last modified: 18 Jun 2018 16:31

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