Articles | Volume 5-opsr
https://doi.org/10.5194/sp-5-opsr-8-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/sp-5-opsr-8-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
02 Jun 2025
| OPSR | Chapter 4.2
| 02 Jun 2025 | OPSR | Chapter 4.2
Merging and serving ocean observations: a description of marine data aggregators
Antonio Novellino
CORRESPONDING AUTHOR
ETT SpA, Genoa, Italy
Pierre-Yves Le Traon
Mercator Ocean International, Toulouse, France
Andy Moore
Physical & Biological Sciences Division, Ocean Sciences Department Institute of Marine Sciences, Institute of Marine Sciences, University of California Santa Cruz, Santa Cruz, California, USA
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William J. Crawford, Polly J. Smith, Ralph F. Milliff, Jerome Fiechter, Christopher K. Wikle, Christopher A. Edwards, and Andrew M. Moore
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V. Turpin, E. Remy, and P. Y. Le Traon
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F. Ninove, P.-Y. Le Traon, E. Remy, and S. Guinehut
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K. von Schuckmann, J.-B. Sallée, D. Chambers, P.-Y. Le Traon, C. Cabanes, F. Gaillard, S. Speich, and M. Hamon
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P. Y. Le Traon
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Cited articles
Belbéoch, M., Jiang, L., Kramp, M., Krieger, M., Lizé, A., Rusciano, E., and Turpin, V.: International coordination of the in situ met-ocean observing networks, 9th EuroGOOS International conference, Shom, Ifremer, EuroGOOS AISBL, 3–5 May 2021, Brest, France, https://hal.science/hal-03328358v1/file/EuroGOOS2021_extended_abstract_Belbeoch.pdf (last access: 27 July 2024), 2022.
Corredor, J. E.: Coastal Ocean Observing – Platforms, Sensors and Systems, Springer Cham, XIV, 159, https://doi.org/10.1007/978-3-319-78352-9, 2018.
Martín Míguez, B., Novellino, A., Vinci, M., Claus, S., Calewaert, J. B., Vallius, H., Schmitt, T., Pititto, A., Giorgetti, A., Askew, N., Iona, S., Schaap, D., Pinardi, N., Harpham, Q., Kater, B., Populus, J., She, J., Palazov, A. V., McMeel, O., Oset, P., Lear, D., Manzella, G. M. R., Gorringe, P., Simoncelli, S., Larkin, K., Holdsworth, N., Arvanitidis, C. D., Molina, J. M. E., Chaves Montero, M., Herman, P. M. J., and Hernandez, F.: The European Marine Observation and Data Network (EMODnet): Visions and Roles of the Gateway to Marine Data in Europe, Front. Mar. Sci., 6, 313, https://doi.org/10.3389/fmars.2019.00313, 2019.
Moltmann, T., Turton, J., Zhang, H.-M., Nolan, G., Gouldman, C., Griesbauer, L., Willis, Z., Piniella, Á. M., Barrell, S., Andersson, E., Gallage, C., Charpentier, E., Belbeoch, M., Poli, P., Rea, A., Burger, E. F., Legler, D. M., Lumpkin, R., Meinig, C., O'Brien, K., Saha, K., Sutton, A., Zhang, D., and Zhang, Y.: A Global Ocean Observing System (GOOS), Delivered Through Enhanced Collaboration Across Regions, Communities, and New Technologies, Front. Mar. Sci., 6, 291, https://doi.org/10.3389/fmars.2019.00291, 2019.
Novellino, A., Arnaud, A., Schiller, A., and Wan, L.: End User Applications for Ocean Forecasting: present status description, in: Ocean prediction: present status and state of the art (OPSR), edited by: Álvarez Fanjul, E., Ciliberti, S. A., Pearlman, J., Wilmer-Becker, K., and Behera, S., Copernicus Publications, State Planet, 5-opsr, 25, https://doi.org/10.5194/sp-5-opsr-25-2025, 2025.
O'Brien, K., Heslop, E., and Belbeoch, M.: Observations Coordination Group (OCG) Data Implementation Strategy (2024), GOOS Report No. 296, https://goosocean.org/document/33970 (last access: 19 March 2025), 2024.
Schaap, D. M. A. and Lowry, R. K.: SeaDataNet – Pan-European infrastructure for marine and ocean data management: unified access to distributed data sets, Int. J. Digit. Earth, 3, 50–69, https://doi.org/10.1080/17538941003660974, 2010.
Schaap, D. M. A., Novellino, A., Fichaut, M., and Manzella, G. M. R.: Chapter Three – Data management infrastructures and their practices in Europe, in: Ocean Science Data, Elsevier, 131–193, https://doi.org/10.1016/B978-0-12-823427-3.00007-4, 2022.
Shepherd, I.: European efforts to make marine data more accessible, Ethics in Science and Environmental Politics, 18, 75–81, https://doi.org/10.3354/esep00181, 2018.
Simoncelli, S., Manzella, G. M. R., Storto, A., Pisano, A., Lipizer, M., Barth, A., Myroshnychenko, V., Boyer, T., Troupin, C., Coatanoan, C., Pititto, A., Schlitzer, R., Schaap, D. M. A., and Diggs, S.: Chapter Four – A collaborative framework among data producers, managers, and users, in: Ocean Science Data, Elsevier, 197–280, https://doi.org/10.1016/B978-0-12-823427-3.00001-3, 2022.
Wilkinson, M., Dumontier, M., Aalbersberg, I., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J., Bonino da Silva Santos, L., Bourne, P., Bouwman, J., Brookes, A., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C., Finkers, R., Gonzalez-Beltran, A., Gray, A., Groth, P., Goble, C., Grethe, J., Heringa, J., 't Hoen, P., Hooft, R., Kuhn, T., Kok, R., Kok, J., Lusher, S., Martone, M., Mons, A., Packer, A., Persson, B., Rocca-Serra, P., Roos, M., van Schaik, R., Sansone, S., Schultes, E., Sengstag, T., Slater, T., Strawn, G., Swertz, M., Thompson, M., van der Lei, J., van Mulligen, E., Velterop, J., Waagmeester, A., Wittenburg, P., Wolstencroft, K., Zhao, J., and Mons, B.: The FAIR Guiding Principles for scientific data management and stewardship, Sci. Data 3, 160018, https://doi.org/10.1038/sdata.2016.18, 2016.
Short summary
This paper discusses the vital role of observations in ocean predictions and forecasting, highlighting the need for effective access, management, and integration of data to improve models and decision-making. The paper also explores opportunities for standardizing protocols and the potential of citizen-based, cost-effective data collection methods.
This paper discusses the vital role of observations in ocean predictions and forecasting,...
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