TY - JOUR
T1 - Ocean FAIR data services
AU - Tanhua, Toste
AU - Pouliquen, Sylvie
AU - Hausman, Jessica
AU - O'Brien, Kevin M.
AU - Bricher, Pip
AU - Bruin, Taco de
AU - Buck, Justin J.
AU - Burger, Eugene F.
AU - Carval, Thierry
AU - Casey, Kenneth S.
AU - Diggs, Steve
AU - Giorgetti, Alessandra
AU - Glaves, Helen
AU - Harscoat, Valerie
AU - Kinkade, Danie
AU - Muelbert, Jose H.
AU - Novellino, Antonio
AU - Pfeil, Benjamin G.
AU - Pulsifer, Peter
AU - Van de Putte, Anton P.
AU - Robinson, Erin
AU - Shaap, Dick
AU - Smirnov, Alexander
AU - Smith, Neville
AU - Snowden, Derrick P.
AU - Spears, Tobias
AU - Stall, Shelley
AU - Tacoma, Marten
AU - Thijsse, Peter
AU - Tronstad, Stein
AU - Vandenberghe, Thomas
AU - Wengren, Micha
AU - Wyborn, Lesley
AU - Zhao, Zhiming
N1 - Publisher Copyright:
© 2019 Tanhua, Pouliquen, Hausman, O'Brien, Bricher, de Bruin, Buck, Burger, Carval, Casey, Diggs, Giorgetti, Glaves, Harscoat, Kinkade, Muelbert, Novellino, Pfeil, Pulsifer, Van de Putte, Robinson, Shaap, Smirnov, Smith, Snowden, Spears, Stall, Tacoma, Thijsse, Tronstad, Vandenberghe, Wengren, Wyborn and Zhao.
PY - 2019
Y1 - 2019
N2 - 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 secure 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 increases dramatically. For instance, there are more than 70 data catalogues 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.
AB - 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 secure 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 increases dramatically. For instance, there are more than 70 data catalogues 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.
KW - Data managament
KW - Data services
KW - FAIR
KW - Interoperability
KW - Ocean
KW - Ocean observing
KW - Standardization
UR - http://www.scopus.com/inward/record.url?scp=85069792961&partnerID=8YFLogxK
U2 - 10.3389/fmars.2019.00440
DO - 10.3389/fmars.2019.00440
M3 - Review article
SN - 2296-7745
VL - 6
JO - Frontiers in Marine Science
JF - Frontiers in Marine Science
IS - JUL
M1 - 440
ER -