Disrupting data sharing for a healthier ocean

Type Article
Date 2019-11
Language English
Author(s) Pendleton Linwood H1, 2, 3, 4, Beyer Hawthorne3, Estradivari 5, Grose Susan O4, Hoegh-Guldberg Ove3, Karcher Denis B4, Kennedy Emma3, Llewellyn Lyndon6, Nys CecileORCID4, Shapiro Aurélie1, Jain Rahul7, Kuc Katarzyna7, Leatherland Terry7, O’hainnin Kira7, Olmedo Guillermo7, Seow Lynette7, Tarsel Mick7, Blasiak Robert
Affiliation(s) 1 : World Wildlife Fund, 1250 24th Street NW, Washington, DC, USA
2 : The Nicholas Institute for Environmental Policy, Duke University, 2117 Campus Drive, P.O. Box 90335, Durham, NC, USA
3 : Global Change Institute, Research Road, The University of Queensland, St. Lucia QLD, Australia
4 : Ifremer, CNRS, UMR 6308, AMURE, IUEM, University of Western Brittany, Technopôle Brest-Iroise, Rue Dumont D' Urville, Plouzané, France
5 : Conservation Science Unit, WWF - Indonesia, Graha Simatupang Tower 2 Unit C, 7th - 11th Floor, Jalan Letjen TB Simatupang Jakarta, Indonesia
6 : Australian Institute of Marine Science, Townsville, 1526 Cape Cleveland Road, Cape Cleveland QLD, Australia
7 : IBM Corporation, Corporate Citizenship & Corporate Affairs, 2455 South Road, Poughkeepsie, New York, USA
Source Ices Journal Of Marine Science (1054-3139) (Oxford University Press (OUP)), 2019-11 , Vol. 76 , N. 6 , P. 1415-1423
DOI 10.1093/icesjms/fsz068
WOS© Times Cited 20
Keyword(s) combinatorial machine, collaboration, data aggregation, data sharing, data uploading, ocean conservation

Ocean ecosystems are in decline, yet we also have more ocean data, and more data portals, than ever before. To make effective decisions regarding ocean management, especially in the face of global environmental change, we need to make the best use possible of these data. Yet many data are not shared, are hard to find, and cannot be effectively accessed. We identify three classes of challenges to data sharing and use: uploading, aggregating, and navigating. While tremendous advances have occurred to improve ocean data operability and transparency, the effect has been largely incremental. We propose a suite of both technical and cultural solutions to overcome these challenges including the use of natural language processing, automatic data translation, ledger-based data identifiers, digital community currencies, data impact factors, and social networks as ways of breaking through these barriers. One way to harness these solutions could be a combinatorial machine that embodies both technological and social networking solutions to aggregate ocean data and to allow researchers to discover, navigate, and download data as well as to connect researchers and data users while providing an open-sourced backend for new data tools.

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Pendleton Linwood H, Beyer Hawthorne, Estradivari, Grose Susan O, Hoegh-Guldberg Ove, Karcher Denis B, Kennedy Emma, Llewellyn Lyndon, Nys Cecile, Shapiro Aurélie, Jain Rahul, Kuc Katarzyna, Leatherland Terry, O’hainnin Kira, Olmedo Guillermo, Seow Lynette, Tarsel Mick, Blasiak Robert (2019). Disrupting data sharing for a healthier ocean. Ices Journal Of Marine Science, 76(6), 1415-1423. Publisher's official version : https://doi.org/10.1093/icesjms/fsz068 , Open Access version : https://archimer.ifremer.fr/doc/00500/61162/