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The goal ofdafishr is to provide an easy way to download VesselMonitoring System (VMS) and analyse data from the Mexican FisheryCommission available atDatos Abiertosinitiative searching for “Sistema de Monitoreo Satelital Embarcaciones”in Spanish. Within the package you can find tools that allows you todownload VMS data, wrangle and clean raw data, and analyse tracks.

The VMS stands for Vessel Monitoring System, which is adopted onindustrial fishing vessels to monitor fishing activity. These data arevery important to understand the fishing activity within a country, itsdynamics in time and space, and to monitor the activity within MarineProtected Areas (MPAs). Along with data from VMS we also provide layersthat are used to clean and map the information. We are currently workingon a scientific manuscript which will be related to this work that iscurrently under review.

You can follow the instruction below using a sample dataset that comesalong with the package, or you can use the function on data you candownload yourself by using thevms_download() function. See ?vms_datafor details on its usage.

install.packages("dafishr")

You can install development version ofdafishr with:

# install.packages("devtools")devtools::install_github("CBMC-GCMP/dafishr")

If you haven’tdevtools package previously installed just delete thecomment # from the code above and run both lines.

You can start usingdafishr suit of functions using thesample_dataset provided with this package, or you can download yourown raw-data files using thevms_download() function. Further detailsare explained in thedocumentationvignette for thispackage. You can see the suit of data and functions available within thepackagehere.

This package follows thetidyverse programming style and depends onseveral package of the family that will be downloaded automatically onceinstalled. Some functions can be applied to a more general object, butthese are specifically built for the format of the raw data of the VMSform CONAPESCA (Mexican Fishery Commission). Therefore, these packagefocused mostly on that format to help user analyse and report data.

The workflow provided here is a work in progress and there are probablysome errors we haven’t spotted or considered up to now. If you feel youcan contribute to this effort feel free to do so by creating a pullrequest. If you are an undergrad and you which to help or developscientific projects using this data you are welcome to contact us.Please, find contact information of the main authorhere, or viatwitter.