Managing and Consuming Completeness Information for RDF Data Sources

The ever increasing amount of Semantic Web data gives rise to the question: How complete is the data? Though generally data on the Semantic Web is incomplete, many parts of data are indeed complete, such as the children of Barack Obama and the crew of Apollo 11. This thesis aims to study how to manage and consume completeness information about Semantic Web data. In particular, we first discuss how completeness information can guarantee the completeness of query answering. Next, we propose optimization techniques of completeness reasoning and conduct experimental evaluations to show the feasibility of our approaches. We also provide a technique to check the soundness of queries with negation via reduction to query completeness checking. We further enrich completeness information with timestamps, enabling query answers to be checked up to when they are complete. We then introduce two demonstrators, i.e., CORNER and COOL-WD, to show how our completeness framework can be realized. Finally, we investigate an automated method to generate completeness statements from text on the Web via relation cardinality extraction

Certain answers for SPARQL with blank nodes

Blank nodes in RDF graphs can be used to represent values known to exist but whose identity remains unknown. A prominent example of such usage can be found in the Wikidata dataset where, e.g., the author of Beowulf is given as a blank node. However, while SPARQL considers blank nodes in a query as existentials, it treats blank nodes in RDF data more like constants. Running SPARQL queries over datasets with unknown values may thus lead to counter-intuitive results, which may make the standard SPARQL semantics unsuitable for datasets with existential blank nodes. We thus explore the feasibility of an alternative SPARQL semantics based on certain answers. In order to estimate the performance costs that would be associated with such a change in semantics for current implementations, we adapt and evaluate approximation techniques proposed in a relational database setting for a core fragment of SPARQL. To further understand the impact that such a change in semantics may have on query solutions, we analyse how this new semantics would affect the results of user queries over Wikidata