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A-posteriori provenance-enabled linking of publications and datasets via crowdsourcing

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
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
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 At Second Workshop on Linking and Contextualizing Publications and Datasets, 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

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More information

Published date: 12 September 2014
Venue - Dates: Second Workshop on Linking and Contextualizing Publications and Datasets, 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
ORCID for Elena Simperl: ORCID iD orcid.org/0000-0003-1722-947X
ORCID for Luc Moreau: ORCID iD orcid.org/0000-0002-3494-120X

Catalogue record

Date deposited: 01 Dec 2014 09:52
Last modified: 17 Jul 2017 21:44

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Contributors

Author: Laura Dragan
Author: Markus Luczak-Rösch
Author: Bettina Berendt
Author: Elena Simperl ORCID iD
Author: Heather S. Packer
Author: Luc Moreau ORCID iD

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