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A-posteriori Provenance-enabled Linking of Publications and Datasets Via Crowdsourcing

Drăgan, Laura, Luczak-rösch, Markus, Simperl, Elena, Packer, Heather and Moreau, Luc (2015) A-posteriori Provenance-enabled Linking of Publications and Datasets Via Crowdsourcing D-Lib Magazine, 21, (1/2) (doi:10.1045/january2015-contents).

Record type: Article


In this paper we present opportunities to leverage crowdsourcing for a-posteriori capturing dataset citation graphs. We describe a user study we carried out, which applied a possible crowdsourcing technique to collect this information from domain experts. We propose to publish the results as Linked Data, using the W3C PROV standard, and we demonstrate how to do this with the Web-based application we built for the study. Based on the results and feedback from this first study, we introduce a two-layered approach that combines information extraction technology and crowdsourcing in order to achieve both scalability (through the use of automatic tools) and accuracy (via human intelligence). In addition, non-experts can become involved in the process.

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Published date: 2015
Organisations: Web & Internet Science, Electronics & Computer Science


Local EPrints ID: 410309
ISSN: 1082-9873
PURE UUID: 429debe8-d857-4347-b5b1-a74e4e496380
ORCID for Elena Simperl: ORCID iD
ORCID for Luc Moreau: ORCID iD

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Date deposited: 07 Jun 2017 04:01
Last modified: 17 Jul 2017 13:34

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Author: Laura Drăgan
Author: Markus Luczak-rösch
Author: Elena Simperl ORCID iD
Author: Heather Packer
Author: Luc Moreau ORCID iD

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