Quality Control and Pre-Analysis Treatment of the Environmental Datasets Collected by an Internet Operated Deep-Sea Crawler during Its Entire 7-Year Long Deployment (2009-2016).

Autor: Chatzievangelou D; Department of Physics and Earth Sciences, Jacobs University, 28759 Bremen, Germany., Aguzzi J; Instituto de Ciencias del Mar (ICM-CSIC), 08003 Barcelona, Spain.; Stazione Zoologica Anton Dohrn (SZN), 80122 Naples, Italy., Scherwath M; Ocean Networks Canada, University of Victoria, Queenswood Campus, Victoria, BC V8N 1V8, Canada., Thomsen L; Department of Physics and Earth Sciences, Jacobs University, 28759 Bremen, Germany.
Jazyk: angličtina
Zdroj: Sensors (Basel, Switzerland) [Sensors (Basel)] 2020 May 25; Vol. 20 (10). Date of Electronic Publication: 2020 May 25.
DOI: 10.3390/s20102991
Abstrakt: Deep-sea environmental datasets are ever-increasing in size and diversity, as technological advances lead monitoring studies towards long-term, high-frequency data acquisition protocols. This study presents examples of pre-analysis data treatment steps applied to the environmental time series collected by the Internet Operated Deep-sea Crawler "Wally" during a 7-year deployment (2009-2016) in the Barkley Canyon methane hydrates site, off Vancouver Island (BC, Canada). Pressure, temperature, electrical conductivity, flow, turbidity, and chlorophyll data were subjected to different standardizing, normalizing, and de-trending methods on a case-by-case basis, depending on the nature of the treated variable and the range and scale of the values provided by each of the different sensors. The final pressure, temperature, and electrical conductivity (transformed to practical salinity) datasets are ready for use. On the other hand, in the cases of flow, turbidity, and chlorophyll, further in-depth processing, in tandem with data describing the movement and position of the crawler, will be needed in order to filter out all possible effects of the latter. Our work evidences challenges and solutions in multiparametric data acquisition and quality control and ensures that a big step is taken so that the available environmental data meet high quality standards and facilitate the production of reliable scientific results.
Databáze: MEDLINE
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