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Publication - Ocean FAIR Data Services

Toste Tanhua, Sylvie Pouliquen, et al., 2019. Ocean FAIR Data Services. Frontiers in Marine Science 6
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Well-founded data management systems are of vital importance for ocean observing systems as they ensure that essential data are not only collected but also retained and made accessible for analysis and application by current and future users. Effective data management requires collaboration across activities including observations, metadata and data assembly, quality assurance and control (QA/QC), and data publication that enables local and interoperable discovery and access and secures archiving that guarantees long-term preservation. To achieve this, data should be findable, accessible, interoperable, and reusable (FAIR). Here, we outline how these principles apply to ocean data and illustrate them with a few examples. In recent decades, ocean data managers, in close collaboration with international organizations, have played an active role in the improvement of environmental data standardization, accessibility, and interoperability through different projects, enhancing access to observation data at all stages of the data life cycle and fostering the development of integrated services targeted to research, regulatory, and operational users. As ocean observing systems evolve and an increasing number of autonomous platforms and sensors are deployed, the volume and variety of data increase dramatically. For instance, there are more than 70 data catalogs that contain metadata records for the polar oceans, a situation that makes comprehensive data discovery beyond the capacity of most researchers. To better serve research, operational, and commercial users, more efficient turnaround of quality data in known formats and made available through Web services is necessary. In particular, automation of data workflows will be critical to reduce friction throughout the data value chain. Adhering to the FAIR principles with free, timely, and unrestricted access to ocean observation data is beneficial for the originators, has obvious benefits for users, and is an essential foundation for the development of new services made possible with big data technologies.


Toste Tanhua
Sylvie Pouliquen
Jessica Hausman
Kevin O’Brien
Pip Bricher
Justin J. H. Buck
Eugene F. Burger
Thierry Carval
Kenneth S. Casey
Steve Diggs
Alessandra Giorgetti
Helen Glaves
Valerie Harscoat
Danie Kinkade
Jose H. Muelbert
Antonio Novellino
Benjamin Pfeil
Peter L. Pulsifer
Anton Van de Putte
Erin Robinson
Dick Schaap
Alexander Smirnov
Neville Smith
Derrick Snowden
Tobias Spears
Shelley Stall
Peter Thijsse
Stein Tronstad
Thomas Vandenberghe
Micah Wengren
Lesley Wyborn
Zhiming Zhao


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Doi: 10.3389/fmars.2019.00440 | UUID: 4fb810a1-b98c-5dd3-a5f6-bddf9022ff89 | Version:1 | Added on: 23 October 2020 09:41