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Data_Sheet_2_Best Practice Data Standards for Discrete Chemical Oceanographic Observations.docx (1.91 MB)

Data_Sheet_2_Best Practice Data Standards for Discrete Chemical Oceanographic Observations.docx

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posted on 2022-01-21, 10:04 authored by Li-Qing Jiang, Denis Pierrot, Rik Wanninkhof, Richard A. Feely, Bronte Tilbrook, Simone Alin, Leticia Barbero, Robert H. Byrne, Brendan R. Carter, Andrew G. Dickson, Jean-Pierre Gattuso, Dana Greeley, Mario Hoppema, Matthew P. Humphreys, Johannes Karstensen, Nico Lange, Siv K. Lauvset, Ernie R. Lewis, Are Olsen, Fiz F. Pérez, Christopher Sabine, Jonathan D. Sharp, Toste Tanhua, Thomas W. Trull, Anton Velo, Andrew J. Allegra, Paul Barker, Eugene Burger, Wei-Jun Cai, Chen-Tung A. Chen, Jessica Cross, Hernan Garcia, Jose Martin Hernandez-Ayon, Xinping Hu, Alex Kozyr, Chris Langdon, Kitack Lee, Joe Salisbury, Zhaohui Aleck Wang, Liang Xue

Effective data management plays a key role in oceanographic research as cruise-based data, collected from different laboratories and expeditions, are commonly compiled to investigate regional to global oceanographic processes. Here we describe new and updated best practice data standards for discrete chemical oceanographic observations, specifically those dealing with column header abbreviations, quality control flags, missing value indicators, and standardized calculation of certain properties. These data standards have been developed with the goals of improving the current practices of the scientific community and promoting their international usage. These guidelines are intended to standardize data files for data sharing and submission into permanent archives. They will facilitate future quality control and synthesis efforts and lead to better data interpretation. In turn, this will promote research in ocean biogeochemistry, such as studies of carbon cycling and ocean acidification, on regional to global scales. These best practice standards are not mandatory. Agencies, institutes, universities, or research vessels can continue using different data standards if it is important for them to maintain historical consistency. However, it is hoped that they will be adopted as widely as possible to facilitate consistency and to achieve the goals stated above.

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