Data Integration Using Correlated Concepts
by Lushan Han
Tuesday, October 13, 2009, 10:15am - Tuesday, October 13, 2009, 11:30am
ITE 325 - B
Lushan Han will talk about "Data Integration Using Correlated Concepts".
Abstract:
The Semantic Web language RDF was designed to unambiguously define and use ontologies to encode data and knowledge on the Web. It is difficult, however, to write complex RDF statements and queries because doing so requires familiarity with the appropriate ontologies and the terms they define. While ontologies have been developed for various branches of the sciences, their use remains limited. We describe a framework that eases the experience of authoring and querying RDF data, in which we focus on automatically finding a set of appropriate Semantic Web ontology terms from a set of words used as the labels of nodes and edges in an incoming semantic graph. Such a system can lead to a greater use of Semantic Web tools and machinery in the sciences, facilitating collaboration and discovery.
Participate remotely via dimdim. After 10:15, click on JOIN MEETING and enter 'ebiquity' for the meeting name.
Abstract:
The Semantic Web language RDF was designed to unambiguously define and use ontologies to encode data and knowledge on the Web. It is difficult, however, to write complex RDF statements and queries because doing so requires familiarity with the appropriate ontologies and the terms they define. While ontologies have been developed for various branches of the sciences, their use remains limited. We describe a framework that eases the experience of authoring and querying RDF data, in which we focus on automatically finding a set of appropriate Semantic Web ontology terms from a set of words used as the labels of nodes and edges in an incoming semantic graph. Such a system can lead to a greater use of Semantic Web tools and machinery in the sciences, facilitating collaboration and discovery.
Participate remotely via dimdim. After 10:15, click on JOIN MEETING and enter 'ebiquity' for the meeting name.