There is no credibility insurance measure for the information provided by the Web. In most cases, information cannot be checked for accuracy. Semantic Web technologies aimed to give structure and sense to information published on the Web and to provide us with a machine-readable data format for interlinked data. However, Semantic Web standards do not offer the possibility to represent and attach uncertainty to such data in a way allowing the reasoning over the latter. Moreover, uncertainty is context-dependent and may be represented by multiple theories which apply different calculi. In this paper, we present a new vocabulary and a framework for handling generic uncertainty representation and reasoning. The meta-Uncertainty vocabulary offers a way to represent uncertainty theories and annotate Linked Data with uncertainty information. We provide the tools to represent uncertainty calculi linked to the previous theories using the LDScript function scripting language. Moreover, we describe the semantics of contexts in uncertainty reasoning with meta-uncertainty. We describe the mapping between RDF triples and their uncertainty information, and we demonstrate the effect on the query writing process in Corese. We discuss the translatability of uncertainty theories and, finally, the negotiation of an answer annotated with uncertainty information. CCS CONCEPTS • Information systems → Uncertainty; Web data description languages; Ontologies; • Theory of computation → Incomplete, inconsistent, and uncertain databases.

The open nature of the Web exposes it to the many imperfections of our world. As a result, before we can use knowledge obtained from the Web, we need to represent that fuzzy, vague, ambiguous and uncertain information. Current standards of the Semantic Web and Linked Data do not support such a representation in a formal way and independently of any theory. We present a new vocabulary and a framework to capture and handle uncertainty in the Semantic Web. First, we define a vocabulary for uncertainty and explain how it allows the publishing of uncertainty information relying on different theories. In addition, we introduce an extension to represent and exchange calculations involved in the evaluation of uncertainty. Then we show how this model and its operational definitions support querying a data source containing different levels of uncertainty metadata. Finally, we discuss the perspectives with a view on supporting reasoning over uncertain linked data.

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