Querying for Meta Knowledge
The Semantic Web is based on accessing and reusing RDF data from many di.erent sources, which one may assign di.erent levels of authority and credibility. Existing Semantic Web query languages, like SPARQL, have targeted the retrieval, combination and reuse of facts, but have so far ignored all aspects of meta knowledge, such as origins, authorship, recency or certainty of data, to name but a few. In this paper, we present an original, generic, formalized and implemented approach formanaging many dimensions of meta knowledge, like source, authorship, certainty and others. The approach re-uses existing RDF modeling possibilities in order to represent meta knowledge. Then, it extends SPARQL query processing in such a way that given a SPARQL query for data, one may request meta knowledge without modifying the original query. Thus, our approach achieves highly flexible and automatically coordinated querying for data and meta knowledge, while completely separating the two areas of concern.
Semantic Web SPARQL RDF
Bernhard Schueler Sergej Sizov Steffen Staab Duc Thanh Tran
ISWeb — Information Systems and Semantic Web University of Koblenz-Landau,Germany Institute AIFB University of Karlsruhe,Germany
国际会议
第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)
北京
英文
2008-04-21（万方平台首次上网日期，不代表论文的发表时间）