Disrupting data sharing for a healthier ocean

【Author】 Pendleton, Linwood H.; Beyer, Hawthorne; Estradivari; Grose, Susan O.; Hoegh-Guldberg, Ove; Karcher, Denis B.; Kennedy, Emma; Llewellyn, Lyndon; Nys, Cecile; Shapiro, Aurelie; Jain, Rahul; Kuc, Katarzyna; Leatherland, Terry; O'Hainnin, Kira; Olmedo, Guillermo; Seow, Lynette; Tarsel, Mick

【Source】ICES JOURNAL OF MARINE SCIENCE

【影响因子】3.906

【Abstract】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.

【Keywords】combinatorial machine; collaboration; data aggregation; data sharing; data uploading; ocean conservation

【发表时间】2019 NOV-DEC

【收录时间】2022-01-02

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