A-posteriori Provenance-enabled Linking of Publications and Datasets Via Crowdsourcing
A-posteriori Provenance-enabled Linking of Publications and Datasets Via Crowdsourcing
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.
Drăgan, Laura
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Luczak-rösch, Markus
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Simperl, Elena
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Packer, Heather
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Moreau, Luc
033c63dd-3fe9-4040-849f-dfccbe0406f8
2015
Drăgan, Laura
c2f59b0b-db7d-4259-8181-bf05bdc6dd35
Luczak-rösch, Markus
6cfe587f-e02c-48e8-b2b8-543952ab50a7
Simperl, Elena
40261ae4-c58c-48e4-b78b-5187b10e4f67
Packer, Heather
8d9d8e4e-c2f4-405b-83dd-0b4c04615f65
Moreau, Luc
033c63dd-3fe9-4040-849f-dfccbe0406f8
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).
Abstract
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.
Text
CrowdsourcingProvenance
- Accepted Manuscript
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e-pub ahead of print date: January 2015
Published date: 2015
Organisations:
Web & Internet Science, Electronics & Computer Science
Identifiers
Local EPrints ID: 410309
URI: http://eprints.soton.ac.uk/id/eprint/410309
ISSN: 1082-9873
PURE UUID: 429debe8-d857-4347-b5b1-a74e4e496380
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Date deposited: 07 Jun 2017 04:01
Last modified: 15 Mar 2024 14:10
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Contributors
Author:
Laura Drăgan
Author:
Markus Luczak-rösch
Author:
Heather Packer
Author:
Luc Moreau
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