Ontologies on the MOVE

Wouters, C; Dillon, TS; Rahayu, W; Chang, E; Meersman, R

Ontologies on the MOVE

Wouters, C Dillon, TS Rahayu, W Chang, E Meersman, R

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Publisher:: Springer-Verlag Berlin
Publication Type:: Conference Proceeding
Citation:: Database Systems For Advanced Applications, 2004, 2973 pp. 812 - 823
Issue Date:: 2004-01

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Field	Value	Language
dc.contributor.author	Wouters, C	en_US
dc.contributor.author	Dillon, TS	en_US
dc.contributor.author	Rahayu, W	en_US
dc.contributor.author	Chang, E	en_US
dc.contributor.author	Meersman, R	en_US
dc.contributor.editor	Lee, Y	en_US
dc.contributor.editor	Li, J	en_US
dc.contributor.editor	Whang, KY	en_US
dc.contributor.editor	Lee, D	en_US
dc.date	2004-03-17	en_US
dc.date.issued	2004-01	en_US
dc.identifier.citation	Database Systems For Advanced Applications, 2004, 2973 pp. 812 - 823	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/1824
dc.description.abstract	The semantic web depends heavily on ontologies, as they provide information about the structures used. Ideally, these ontologies would be static, but in reality they are very much dynamic. This paper addresses the issues that arise from having large ontologies and their automatically generated materialized ontology views, as well as how quality can be maintained in the materialized views. We use the notion of database views to extract ontologies from large base ontologies. A framework is required to consider variations between standards, and differences in user requirements. MOVE, the Materialized Ontology View Extractor will be discussed as an architecture that offers a solution to these problems.	en_US
dc.publisher	Springer-Verlag Berlin	en_US
dc.relation.ispartof	Database Systems For Advanced Applications	en_US
dc.relation.ispartof	Database Systems for Advanced Applications	en_US
dc.relation.isbasedon	10.1007/978-3-540-24571-1_71	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Ontologies on the MOVE	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2973	en_US
utslib.location	Berlin	en_US
utslib.location.activity	Jeju Island, Korea	en_US
utslib.for	0804 Data Format	en_US
dc.location.activity	Jeju Island, Korea	en_US
dc.location.activity	Rome, Italy
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Systems, Management and Leadership
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.place-of-publication	Berlin	en_US
pubs.start-date	2004-03-17	en_US
pubs.volume	2973	en_US

Abstract:

The semantic web depends heavily on ontologies, as they provide information about the structures used. Ideally, these ontologies would be static, but in reality they are very much dynamic. This paper addresses the issues that arise from having large ontologies and their automatically generated materialized ontology views, as well as how quality can be maintained in the materialized views. We use the notion of database views to extract ontologies from large base ontologies. A framework is required to consider variations between standards, and differences in user requirements. MOVE, the Materialized Ontology View Extractor will be discussed as an architecture that offers a solution to these problems.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/1824