Data Provenance and Believability in the Semantic Web
نویسندگان
چکیده
In the semantic Web, human and software agents can link data and combine them to create new data. In this context, the representation and management of data provenance is crucial. Data provenance helps determine the believability of data, which is an important aspect of data quality. This paper focuses on the representation of data provenance in the Web of linked data, and the use of provenance information to measure the believability of data. We present our provenance model and investigate how the concepts of this model can be represented in the semantic Web using existing languages and vocabularies to measure data believability. To our knowledge, our approach, applied in this paper, is the first to develop a precise, systematic approach to measuring data believability and making explicit use of provenance-based measurements in the Web of linked data.
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