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Supporting open dataset publication decisions based on Open Source Software reuse

Supporting open dataset publication decisions based on Open Source Software reuse
Supporting open dataset publication decisions based on Open Source Software reuse

Publishing and maintaining open data is a costly task for public institutions, that becomes even more challenging in the context of Smart Cities, where large amounts of varied data are generated from different domains. To optimize resources, they should prioritize the publication and maintenance of datasets most likely to generate social and economic impact. However, there is currently a lack of decision-support tools to help public sector data publishers to evaluate datasets on the light of their particular reuse goals. In this paper, we propose to suggest to data publishers the dataset categories with most potential impact, based on the impact of already published datasets of the same category. To measure impact, we propose a set of indicators based on the amount and quality of Open Source Software projects that use datasets. To aggregate indicators according to specific reuse goals, we provide an Analytic-Hierarchy-Process based tool.

1613-0073
Prieto, Alvaro E.
cedd8db0-5f48-47a4-b014-3f634c7cb4ed
Mazón, Jose Norberto
9fc718d4-c76f-4e48-8889-eb0cb488b0eb
Lozano-Tello, Adolfo
e4f188d2-163c-4d9e-99e0-0c20eb505ee8
Ibáñez, Luis Daniel
65a2e20b-74a9-427d-8c4c-2330285153ed
Prieto, Alvaro E.
cedd8db0-5f48-47a4-b014-3f634c7cb4ed
Mazón, Jose Norberto
9fc718d4-c76f-4e48-8889-eb0cb488b0eb
Lozano-Tello, Adolfo
e4f188d2-163c-4d9e-99e0-0c20eb505ee8
Ibáñez, Luis Daniel
65a2e20b-74a9-427d-8c4c-2330285153ed

Prieto, Alvaro E., Mazón, Jose Norberto, Lozano-Tello, Adolfo and Ibáñez, Luis Daniel (2018) Supporting open dataset publication decisions based on Open Source Software reuse. CEUR Workshop Proceedings, 2062.

Record type: Article

Abstract

Publishing and maintaining open data is a costly task for public institutions, that becomes even more challenging in the context of Smart Cities, where large amounts of varied data are generated from different domains. To optimize resources, they should prioritize the publication and maintenance of datasets most likely to generate social and economic impact. However, there is currently a lack of decision-support tools to help public sector data publishers to evaluate datasets on the light of their particular reuse goals. In this paper, we propose to suggest to data publishers the dataset categories with most potential impact, based on the impact of already published datasets of the same category. To measure impact, we propose a set of indicators based on the amount and quality of Open Source Software projects that use datasets. To aggregate indicators according to specific reuse goals, we provide an Analytic-Hierarchy-Process based tool.

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More information

Accepted/In Press date: 20 January 2018
e-pub ahead of print date: 15 February 2018
Published date: 2018
Additional Information: added acceptance date. Author seemed tot hink because paper has cc-by-nc-nd 4.0 licence it is open access ?

Identifiers

Local EPrints ID: 420667
URI: https://eprints.soton.ac.uk/id/eprint/420667
ISSN: 1613-0073
PURE UUID: 03edd21d-aabf-4584-9ca9-1f449f4ff27a

Catalogue record

Date deposited: 11 May 2018 16:30
Last modified: 11 May 2018 16:30

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Contributors

Author: Alvaro E. Prieto
Author: Jose Norberto Mazón
Author: Adolfo Lozano-Tello
Author: Luis Daniel Ibáñez

University divisions

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