A General Framework for Querying Possibilistic RDF Data
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Abstract
Data on the Web is often pervaded with uncertainty. This is due to the openness of the Web and variety of sources which makes reliability of collected data questionable. In this paper, we address the Resource Description Framework (RDF) data uncertainty problem. Uncertainty here is represented by the rich possibility theory. To this end, we describe a general framework for supporting SPARQL-like queries on possibilistic RDF data, that we denote Pi-SPARQL. To describe possibilistic requirements, Pi-SPARQL extends SPARQL in the following two ways. First, it allows expressing possibility degrees to RDF based applications in an easy manner by associating the solutions for graph patterns with possibility measures. Then, Pi-SPARQL proposes appropriate semantics of the solution mappings and evaluation, i.e., it enables users to deal with uncertain RDF data specifications and access the possibility measures associated to the solutions.