In:
Frontiers in Marine Science, Frontiers Media SA, Vol. 10 ( 2023-4-26)
Abstract:
While crucial to ensuring the production of accurate and high-quality data—and to avoid erroneous conclusions—data quality control (QC) in environmental monitoring datasets is still poorly documented. Methods With a focus on annual inter-laboratory comparison (ILC) exercises performed in the context of the French coastal monitoring SOMLIT network, we share here a pragmatic approach to QC, which allows the calculation of systematic and random errors, measurement uncertainty, and individual performance. After an overview of the different QC actions applied to fulfill requirements for quality and competence, we report equipment, accommodation, design of the ILC exercises, and statistical methodology specially adapted to small environmental networks ( & lt;20 laboratories) and multivariate datasets. Finally, the expanded uncertainty of measurement for 20 environmental variables routinely measured by SOMLIT from discrete sampling—including Essential Ocean Variables—is provided. Results, Discussion, Conclusion The examination of the temporal variations (2001–2021) in the repeatability, reproducibility, and trueness of the SOMLIT network over time confirms the essential role of ILC exercises as a tool for the continuous improvement of data quality in environmental monitoring datasets.
Type of Medium:
Online Resource
ISSN:
2296-7745
DOI:
10.3389/fmars.2023.1135446
DOI:
10.3389/fmars.2023.1135446.s001
DOI:
10.3389/fmars.2023.1135446.s002
Language:
Unknown
Publisher:
Frontiers Media SA
Publication Date:
2023
detail.hit.zdb_id:
2757748-X
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