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Data quality control considerations in multivariate environmental monitoring : experience of the French coastal network SOMLIT

Title: Data quality control considerations in multivariate environmental monitoring : experience of the French coastal network SOMLIT
Authors: Breton, E.; Savoye, N.; Rimmelin-Maury, P.; Sautour, B.; Goberville, E.; Lheureux, A.; /Cariou, Thierry; Ferreira, S.; Agogue, H.; Alliouane, S.; Aubert, F.; Aubin, S.; Berthebaud, E.; Blayac, H.; Blondel, L.; Boulart, C.; Bozec, Y.; Bureau, S.; Caillo, A.; Cauvin, A.; Cazes, J. B.; Chasselin, L.; Claquin, P.; Conan, P.; Cordier, M. A.; Costes, L.; Crec'hriou, R.; Crispi, O.; Crouvoisier, M.; David, V.; Del Amo, Y.; De Lary, H.; Delebecq, G.; Devesa, J.; Domeau, A.; Durozier, M.; Emery, C.; Feunteun, E.; Fauchot, J.; Gentilhomme, V.; Geslin, S.; Giraud, M.; Grangere, K.; Gregori, G.; Grossteffan, E.; Gueux, A.; Guillaudeau, J.; Guillou, G.; Harrewyn, M.; Jolly, O.; Jude-Lemeilleur, F.; Labatut, P.; Labourdette, N.; Lachaussee, N.; Lafont, M.; Lagadec, V.; Lambert, C.; Lamoureux, J.; Lanceleur, L.; Lebreton, B.; Lecuyer, E.; Lemeille, D.; Leredde, Y.; Leroux, C.; Leynaert, A.; L'Helguen, S.; Lienart, C.; Mace, E.; Maria, E.; Marie, B.; Marie, D.; Mas, S.; Mendes, F.; Mornet, L.; Mostajir, B.; Mousseau, L.; Nowaczyk, A.; Nunige, S.; Parra, R.; Paulin, T.; Pecqueur, D.; Petit, F.; Pineau, P.; Raimbault, P.; Rigaut-Jalabert, F.; Salmeron, C.; Salter, I.; Sauriau, P. G.; Seuront, L.; Sultan, E.; Valdes, R.; Vantrepotte, V.; Vidussi, F.; /Voron, Florian; Vuillemin, R.; Zudaire, L.; Garcia, N.
Publication Year: 2023
Collection: IRD (Institute de recherche pour le développement): Horizon
Subject Terms: environmental monitoring network; data quality control; inter-laboratory; comparison exercises; measurement uncertainty; analyst performance; multivariate dataset
Subject Geographic: FRANCE; MEDITERRANEE; ATLANTIQUE; MANCHE
Description: Introduction: 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 (
Document Type: text
Language: English
Relation: https://www.documentation.ird.fr/hor/fdi:010088134; fdi:010088134
Availability: https://www.documentation.ird.fr/hor/fdi:010088134
Accession Number: edsbas.5B530455
Database: BASE