Managing Data Provenance in the Semantic Web

Abstract: The Web contains some extremely valuable information; however, often poor quality, inaccurate, irrelevant or fraudulent information can be found. With the increasing amount of data available on the Web, is it becoming more and more difficult to distinguish truth from speculations on the Web. One of the most, if not the most, important criterion used to evaluate the data credibility is the information source, i.e. the data origin. Trust in the information source is a valuable currency users have to value or judge such data. Data popularity, recentness (or the time of validity), reliability, or vagueness ascribed to the data may also help users to judge the validity and appropriateness of information sources. We call this knowledge derived from the data the provenance of the data. Provenance is an important aspect of the Web. It is essential in identifying the suitability, veracity, and reliability of information, and in deciding whether information is to be trusted, reused or even integrated with other information sources. Therefore, models and frameworks for representing, managing, and using provenance in the realm of the Semantic Web technologies and applications are critical required. This dissertation highlights the benefits of the use of provenance in different Web applications and scenarios. In particular, it presents management frameworks for querying and reasoning in the Semantic Web with provenance, and a collection of Semantic Web tools that explore provenance information when ranking and updating caches of Web data. This dissertation aims to prove the importance and benefits of the use of provenance in different Web applications and scenarios. The flexibility of the approaches presented combined with their high scalability makes this dissertation a possible building block for a Semantic Web proof and trust layer. Speaker Bio: Renata Dividino will be giving a PhD test talk on “Managing and Using Data Provenance in the Semantic Web”. She will defend her PhD in the University of Koblenz, Germany, this December. Her reseach interests are Semantic Web, Data and Workflow Provenance, knowledge Representation and Reasoning, AI and Visualization. Renata has worked for several universities and research institutes such as the Fraunhofer IGD, is the world’s leading institute for applied research in Visual Computing, and the DFKI, the German Research Center for Artificial Intelligence.

More information at: https://www.dal.ca/news/events/2016/12/08/managing_data_provenance_in_the_semantic_web_.html