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

• Autores: Laura Dragan, Markus Luczak-Rösch, Bettina Berendt, Elena Simperl, Heather Packer, Luc Moureau
• Localización: D-Lib Magazine, ISSN-e 1082-9873, Vol. 21, Nº. 1-2, 2015
• Idioma: inglés
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• Resumen

  • 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.