Ocean FAIR Data Services
| Type | Article | ||||||||
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| Date | 2019-08 | ||||||||
| Language | English | ||||||||
| Author(s) | Tanhua Toste1, Pouliquen Sylvie 2, Hausman Jessica3, O’brien Kevin4, Bricher Pip5, de Bruin Taco6, Buck Justin J. H.7, Burger Eugene F.8, Carval Thierry2, Casey Kenneth S.9, Diggs Steve10, Giorgetti Alessandra11, Glaves Helen12, Harscoat Valerie2, Kinkade Danie13, Muelbert Jose H.14, Novellino Antonio15, Pfeil Benjamin16, Pulsifer Peter L.17, Van De Putte Anton18, Robinson Erin19, Schaap Dick20, Smirnov Alexander21, Smith Neville22, Snowden Derrick23, Spears Tobias24, Stall Shelley25, Tacoma Marten6, Thijsse Peter20, Tronstad Stein26, Vandenberghe Thomas18, Wengren Micah23, Wyborn Lesley27, Zhao Zhiming28 |
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| Affiliation(s) | 1 : GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany 2 : IFREMER, Plouzané, France 3 : Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States 4 : Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, WA, United States 5 : Southern Ocean Observing System, University of Tasmania, Hobart, TAS, Australia 6 : NIOZ Royal Netherlands Institute for Sea Research, and Utrecht University, Texel, Netherlands 7 : National Oceanography Centre–British Oceanographic Data Centre, Liverpool, United Kingdom 8 : NOAA Pacific Marine Environmental Laboratory, Seattle, WA, United States 9 : NOAA National Centers for Environmental Information, Silver Spring, MD, United States 10 : Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, United States 11 : Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Sgonico, Italy 12 : British Geological Survey, Nottingham, United Kingdom 13 : Woods Hole Oceanographic Institution, Woods Hole, MA, United States 14 : Instituto de Oceanografia, Universidade Federal do Rio Grande, Rio Grande, Brazil 15 : ETT, Genova, Italy 16 : Bjerknes Centre for Climate Research, University of Bergen, Bergen, Norway 17 : National Snow and Ice Data Center, University of Colorado Boulder, Boulder, CO, United States 18 : Royal Belgian Institute for Natural Sciences, Brussels, Belgium 19 : Earth Science Information Partners, Boulder, CO, United States 20 : MARIS Mariene Informatie Service, Voorburg, Netherlands 21 : Arctic Portal, Akureyri, Iceland 22 : GODAE Ocean Services, Melbourne, VIC, Australia 23 : U.S. Integrated Ocean Observing System, Silver Spring, MD, United States 24 : Fisheries and Oceans, Science Branch, Maritimes Region Ocean Data and Information Section, Dartmouth, NS, Canada 25 : American Geophysical Union, Washington, DC, United States 26 : Norwegian Polar Institute, Tromsø, Norway 27 : National Computational Infrastructure, Australian National University, Canberra, ACT, Australia 28 : Informatics Institute, University of Amsterdam, Amsterdam, Netherlands |
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| Source | Frontiers In Marine Science (2296-7745) (Frontiers Media SA), 2019-08 , Vol. 6 , N. 440 , P. 17p. | ||||||||
| DOI | 10.3389/fmars.2019.00440 | ||||||||
| WOS© Times Cited | 53 | ||||||||
| Keyword(s) | FAIR, ocean, data management, data services, ocean observing, standardization, interoperability | ||||||||
| Abstract | 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. |
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