On Provenance of Queries on Semantic Web Data

Assessing the quality of data currently published on the Semantic Web emerges as a crucial need of various applications. Capturing trustworthiness, reputation and reliabil- ity of Semantic Web data manipulated by SPARQL, requires to represent adequate provenance information usually modeled as annotations on source data and propagated to query results along with query evaluation. Alternatively, one can use abstract provenance models to capture the relationship between query results and the source data by taking into account the employed query operators. We argue the benefits of the latter for settings in which the query results are materialized in several repositories and analyzed by multiple users. We investigate the extent to which relational provenance models can be leveraged for SPARQL queries and identify their limitations. Finally, we advocate the need for new provenance models capturing the full expressive power of SPARQL.