Learning from the International Polar Year to Build the Future of Polar Data Management

The research data landscape of the last International Polar Year was dramatically different from its predecessors. Data scientists documented lessons learned about management of large, diverse, and interdisciplinary datasets to inform future development and practices. Improved, iterative, and adapti...

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Published in:Data Science Journal
Main Authors: Mokrane, M, Parsons, M A
Format: Article in Journal/Newspaper
Language:English
Published: Ubiquity Press 2014
Subjects:
Online Access:https://datascience.codata.org/jms/article/view/dsj.IFPDA-15
https://doi.org/10.2481/dsj.IFPDA-15
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spelling ftjdsj:oai:ojs.datascience.codata.org:article/32 2023-05-15T16:53:54+02:00 Learning from the International Polar Year to Build the Future of Polar Data Management Mokrane, M Parsons, M A 2014-10-17 application/pdf https://datascience.codata.org/jms/article/view/dsj.IFPDA-15 https://doi.org/10.2481/dsj.IFPDA-15 eng eng Ubiquity Press https://datascience.codata.org/jms/article/view/dsj.IFPDA-15/32 10.2481/dsj.IFPDA-15 https://datascience.codata.org/jms/article/view/dsj.IFPDA-15 doi:10.2481/dsj.IFPDA-15 Authors who publish with this journal agree to the following terms:Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work. CC-BY Data Science Journal; Vol 13 (2014): Special Issue; PDA88-PDA93 1683-1470 International Polar Year Data management Data curation and stewardship Long-term preservation Open-access Data infrastructure Data ecosystem info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2014 ftjdsj https://doi.org/10.2481/dsj.IFPDA-15 2022-04-13T19:17:24Z The research data landscape of the last International Polar Year was dramatically different from its predecessors. Data scientists documented lessons learned about management of large, diverse, and interdisciplinary datasets to inform future development and practices. Improved, iterative, and adaptive data curation and system development methods to address these challenges will be facilitated by building collaborations locally and globally across the ‘data ecosystem’, thus, shaping and sustaining an international data infrastructure to fulfil modern scientific needs and societal expectations. International coordination is necessary to achieve convergence between domain-specific data systems and hence enable multidisciplinary approaches needed to solve the Global Challenges. Article in Journal/Newspaper International Polar Year Data Science Journal Data Science Journal 13 0 88
institution Open Polar
collection Data Science Journal
op_collection_id ftjdsj
language English
topic International Polar Year
Data management
Data curation and stewardship
Long-term preservation
Open-access
Data infrastructure
Data ecosystem
spellingShingle International Polar Year
Data management
Data curation and stewardship
Long-term preservation
Open-access
Data infrastructure
Data ecosystem
Mokrane, M
Parsons, M A
Learning from the International Polar Year to Build the Future of Polar Data Management
topic_facet International Polar Year
Data management
Data curation and stewardship
Long-term preservation
Open-access
Data infrastructure
Data ecosystem
description The research data landscape of the last International Polar Year was dramatically different from its predecessors. Data scientists documented lessons learned about management of large, diverse, and interdisciplinary datasets to inform future development and practices. Improved, iterative, and adaptive data curation and system development methods to address these challenges will be facilitated by building collaborations locally and globally across the ‘data ecosystem’, thus, shaping and sustaining an international data infrastructure to fulfil modern scientific needs and societal expectations. International coordination is necessary to achieve convergence between domain-specific data systems and hence enable multidisciplinary approaches needed to solve the Global Challenges.
format Article in Journal/Newspaper
author Mokrane, M
Parsons, M A
author_facet Mokrane, M
Parsons, M A
author_sort Mokrane, M
title Learning from the International Polar Year to Build the Future of Polar Data Management
title_short Learning from the International Polar Year to Build the Future of Polar Data Management
title_full Learning from the International Polar Year to Build the Future of Polar Data Management
title_fullStr Learning from the International Polar Year to Build the Future of Polar Data Management
title_full_unstemmed Learning from the International Polar Year to Build the Future of Polar Data Management
title_sort learning from the international polar year to build the future of polar data management
publisher Ubiquity Press
publishDate 2014
url https://datascience.codata.org/jms/article/view/dsj.IFPDA-15
https://doi.org/10.2481/dsj.IFPDA-15
genre International Polar Year
genre_facet International Polar Year
op_source Data Science Journal; Vol 13 (2014): Special Issue; PDA88-PDA93
1683-1470
op_relation https://datascience.codata.org/jms/article/view/dsj.IFPDA-15/32
10.2481/dsj.IFPDA-15
https://datascience.codata.org/jms/article/view/dsj.IFPDA-15
doi:10.2481/dsj.IFPDA-15
op_rights Authors who publish with this journal agree to the following terms:Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
op_rightsnorm CC-BY
op_doi https://doi.org/10.2481/dsj.IFPDA-15
container_title Data Science Journal
container_volume 13
container_issue 0
container_start_page 88
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