Evidence map›Paper›PMID 24932915›Full record

ArticlePloS one2014

VMSbase: an R-package for VMS and logbook data management and analysis in fisheries ecology.

Tommaso Russo, Lorenzo D'Andrea, Antonio Parisi, Stefano Cataudella

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
5.6field-weighted citation impact, top 4% of its field
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

9 citing papers in PubMed, 102 citations in OpenAlex.

  1. Article
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  6. Bottom trawl fishing footprints on the world's continental shelves.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
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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 at 1 institution in 1 country.

Tommaso RussoLaboratory of Experimental Ecology and Aquaculture - Department of Biology - "Tor Vergata" University of Rome, via della Ricerca Scientifica s.n.c., Rome, Italy.
Lorenzo D'AndreaLaboratory of Experimental Ecology and Aquaculture - Department of Biology - "Tor Vergata" University of Rome, via della Ricerca Scientifica s.n.c., Rome, Italy.
Antonio ParisiDepartment of Economics and Finance - Faculty of Economics - "Tor Vergata" University of Rome, Rome, Italy.
Stefano CataudellaLaboratory of Experimental Ecology and Aquaculture - Department of Biology - "Tor Vergata" University of Rome, via della Ricerca Scientifica s.n.c., Rome, Italy.
University of Rome Tor Vergata · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

VMSbase is an R package devised to manage, process and visualize information about fishing vessels activity (provided by the vessel monitoring system--VMS) and catches/landings (as reported in the logbooks). VMSbase is primarily conceived to be user-friendly; to this end, a suite of state-of-the-art analyses is accessible via a graphical interface. In addition, the package uses a database platform allowing large datasets to be stored, managed and processed vey efficiently. Methodologies include data cleaning, that is removal of redundant or evidently erroneous records, and data enhancing, that is interpolation and merging with external data sources. In particular, VMSbase is able to estimate sea bottom depth for single VMS pings using an on-line connection to the National Oceanic and Atmospheric Administration (NOAA) database. It also allows VMS pings to be assigned to whatever geographic partitioning has been selected by users. Standard analyses comprise: 1) métier identification (using a modified CLARA clustering approach on Logbook data or Artificial Neural Networks on VMS data); 2) linkage between VMS and Logbook records, with the former organized into fishing trips; 3) discrimination between steaming and fishing points; 4) computation of spatial effort with respect to user-selected grids; 5) calculation of standard fishing effort indicators within Data Collection Framework; 6) a variety of mapping tools, including an interface for Google viewer; 7) estimation of trawled area. Here we report a sample workflow for the accessory sample datasets (available with the package) in order to explore the potentialities of VMSbase. In addition, the results of some performance tests on two large datasets (1×10(5) and 1×10(6) VMS signals, respectively) are reported to inform about the time required for the analyses. The results, although merely illustrative, indicate that VMSbase can represent a step forward in extracting and enhancing information from VMS/logbook data for fisheries studies.

Indexed as

Databases, FactualEcologyFisheriesSoftwareAnimalsBiodiversityConservation of Natural ResourcesFishes

Identifiers

PMID24932915
PMCPMC4059747
OpenAlexW2053421276

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.