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2011 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies
Approaches to Relating and Integrating Semantic Data from Heterogeneous Sources
Lyon France
August 22-August 27
ISBN: 978-0-7695-4513-4
Integrating and relating heterogeneous data using inference is one of the cornerstones of semantic technologies and there are a variety of ways in which this may be achieved. Cross source relationships can be automatically translated or inferred using the axioms of RDFS/OWL, via user generated rules, or as the result of SPARQL query result transformations. For a given problem it is not always obvious which approach (or combination of approaches) will be the most effective and few guidelines exist for making this choice. This paper discusses these three approaches and demonstrates them using an "acquaintance" relationship drawn from data residing in common RDF information sources such as FOAF and DBLP data stores. The implementation of each approach is described along with practical considerations for their use. Quantitative and qualitative evaluation results of each approach are presented and the paper concludes with initial suggestions for guiding principles to help in selecting an appropriate approach for integrating heterogeneous semantic data sources.
Index Terms:
inference, semantic integration, OWL/RDF, rules, query
Citation:
John Keeney, Aidan Boran, Ivan Bedini, Christopher J. Matheus, Peter F. Patel-Schneider, "Approaches to Relating and Integrating Semantic Data from Heterogeneous Sources," wi-iat, vol. 1, pp.170-177, 2011 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies, 2011
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