Evidence map›Paper›PMID 32466261›Full record

ArticleSensors (Basel, Switzerland)2020

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).

Damianos Chatzievangelou, Jacopo Aguzzi, Martin Scherwath, Laurenz Thomsen

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Damianos ChatzievangelouDepartment of Physics and Earth Sciences, Jacobs University, 28759 Bremen, Germany.ORCID 0000-0001-7512-5105
Jacopo AguzziInstituto de Ciencias del Mar (ICM-CSIC), 08003 Barcelona, Spain.ORCID 0000-0002-1484-8219
Martin ScherwathOcean Networks Canada, University of Victoria, Queenswood Campus, Victoria, BC V8N 1V8, Canada.
Laurenz ThomsenDepartment of Physics and Earth Sciences, Jacobs University, 28759 Bremen, Germany.

Funding

Helmholtz-Gemeinschaft HA-304Ministerio de Ciencia, Innovación y Universidades TEC2017-87861-R
6 · The paper itself

Abstract

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.

Indexed as

Barkley Canyon hydratesdata qualitydata treatmentinternet operated deep-sea crawlerOcean Networks Canada

Identifiers

PMID32466261
PMCPMC7287641

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.