Semantic Web Dog Food

Presented at: 3rd European Semantic Web Conference (ESWC2006)

by Uuangui Lei, Marta Sabou, Vanessa Lopez, Jianhan Zhu, Victoria Uren

Because metadata that underlies semantic web applications is gathered from distributed and heterogeneous data sources, it is important to ensure its quality (i.e., reduce duplicates, spelling errors, ambiguities). However, current infrastructures that acquire and integrate semantic data have only marginally addressed the issue of metadata quality. In this paper we present our metadata acquisition infrastructure, ASDI, which pays special attention to ensuring that high quality metadata is derived. Central to the architecture of ASDI is a verification engine that relies on several semantic web tools to check the quality of the derived data. We tested our prototype in the context of building a semantic web portal for our lab, KMi. An experimental evaluation comparing the automatically extracted data against manual annotations indicates that the verification engine enhances the quality of the extracted semantic metadata.

An Infrastructure for Acquiring High Quality Semantic Metadata was presented at this event.

Keywords: Ontology population / generation, Web data extraction

Resource URI on the dog food server: http://data.semanticweb.org/conference/eswc/2006/paper/lei-sabou
Same as: http://www.eswc2006.org/full-papers/#lei-sabou

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