A-posteriori provenance-enabled linking of publications and datasets via crowdsourcing
A-posteriori provenance-enabled linking of publications and datasets via crowdsourcing
This paper aims to share with the digital library community different opportunities to leverage crowdsourcing for a-posteriori capturing of dataset citation graphs. We describe a practical approach, which exploits one possible crowdsourcing technique to collect these graphs from domain experts and proposes their publication as Linked Data using the W3C PROV standard. Based on our findings from a study we ran during the USEWOD 2014 workshop, we propose a semi-automatic approach that generates metadata by leveraging information extraction as an additional step to crowdsourcing, to generate high-quality data citation graphs. Furthermore, we consider the design implications on our crowdsourcing approach when non-expert participants are involved in the process
Dragan, Laura
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Luczak-Rösch, Markus
6cfe587f-e02c-48e8-b2b8-543952ab50a7
Berendt, Bettina
191543ac-805e-4209-b84c-7d8c42ced4c1
Simperl, Elena
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Packer, Heather S.
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Moreau, Luc
033c63dd-3fe9-4040-849f-dfccbe0406f8
12 September 2014
Dragan, Laura
6d28687f-4aa8-43cc-90dd-7be7381b35e5
Luczak-Rösch, Markus
6cfe587f-e02c-48e8-b2b8-543952ab50a7
Berendt, Bettina
191543ac-805e-4209-b84c-7d8c42ced4c1
Simperl, Elena
40261ae4-c58c-48e4-b78b-5187b10e4f67
Packer, Heather S.
0e86c31f-6460-4bbd-b6ac-c717ee2cbd96
Moreau, Luc
033c63dd-3fe9-4040-849f-dfccbe0406f8
Dragan, Laura, Luczak-Rösch, Markus, Berendt, Bettina, Simperl, Elena, Packer, Heather S. and Moreau, Luc
(2014)
A-posteriori provenance-enabled linking of publications and datasets via crowdsourcing.
Second Workshop on Linking and Contextualizing Publications and Datasets, London, United Kingdom.
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper aims to share with the digital library community different opportunities to leverage crowdsourcing for a-posteriori capturing of dataset citation graphs. We describe a practical approach, which exploits one possible crowdsourcing technique to collect these graphs from domain experts and proposes their publication as Linked Data using the W3C PROV standard. Based on our findings from a study we ran during the USEWOD 2014 workshop, we propose a semi-automatic approach that generates metadata by leveraging information extraction as an additional step to crowdsourcing, to generate high-quality data citation graphs. Furthermore, we consider the design implications on our crowdsourcing approach when non-expert participants are involved in the process
Text
lcpd2014_submission_9.pdf
- Accepted Manuscript
Available under License Other.
More information
Published date: 12 September 2014
Venue - Dates:
Second Workshop on Linking and Contextualizing Publications and Datasets, London, United Kingdom, 2014-09-12
Organisations:
Web & Internet Science
Identifiers
Local EPrints ID: 372128
URI: http://eprints.soton.ac.uk/id/eprint/372128
PURE UUID: 4b52e9bf-cb16-4190-9b39-7cc2acfd478f
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Date deposited: 01 Dec 2014 09:52
Last modified: 14 Mar 2024 18:31
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Contributors
Author:
Laura Dragan
Author:
Markus Luczak-Rösch
Author:
Bettina Berendt
Author:
Heather S. Packer
Author:
Luc Moreau
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