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Linking and Negotiating Uncertainty Theories Over Linked Data

Ahmed El Amine Djebri 1, 2 Andrea Tettamanzi 1 Fabien Gandon 1
1 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : 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.
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https://hal.archives-ouvertes.fr/hal-02064075
Contributor : Ahmed El Amine Djebri <>
Submitted on : Monday, March 11, 2019 - 4:28:08 PM
Last modification on : Thursday, March 5, 2020 - 12:20:30 PM

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Ahmed El Amine Djebri, Andrea Tettamanzi, Fabien Gandon. Linking and Negotiating Uncertainty Theories Over Linked Data. WWW 2019 - LDOW/LDDL Workshop of the World Wide Web Conference, May 2019, San Francisco, United States. ⟨10.1145/3308560.3317074⟩. ⟨hal-02064075⟩

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