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Example data records

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Colin Millar edited this page May 30, 2023 · 23 revisions

See also: Creating a TAF analysis, Bib entries.

This page was based on using the icesTAF package version 4.2.0 dated 2023-03-21.

In this guide

Using a script to download a zip file

We will start with an empty repository

                 
 test_datasets   
  ¦--boot        
  ¦   °--initial 
  ¦       °--data
  ¦--data.R      
  ¦--model.R     
  ¦--output.R    
  °--report.R

Consider the following script that downloads a zip file containing ESRI shapefiles of ICES areas, unzips it and deletes the zip file

filename <- "ICES_areas.zip"
# download and unzip
download(paste0("http://gis.ices.dk/shapefiles/", filename))
unzip(filename)
# delete zip file
unlink(filename)

This code can be used to download shapefiles for use in a TAF assessment by specifying script as the source of the data. This is done by creating the following metadata record in DATA.bib

@Misc{icesareas,
  originator = {ICES},
  year       = {2023},
  title      = {ICES Areas ESRI Shapefile},
  access     = {Public},
  source     = {script},
}

and an accompanying R script. The R script must have the same name as the ‘key’ field. In this case the key is icesareas so the script must be called icesareas.R. The DATA.bib entry can be created using the draft.data function

  draft.data(
    data.files = "icesareas",
    originator = "ICES",
    title = "ICES Areas ESRI Shapefile",
    period = FALSE,
    source = "script",
    file = TRUE
  )

After you have created the script in the boot folder called icesareas.R the directory structure should look like this:

                    
 test_datasets      
  ¦--boot           
  ¦   ¦--DATA.bib   
  ¦   ¦--icesareas.R
  ¦   °--initial    
  ¦       °--data   
  ¦--data.R         
  ¦--model.R        
  ¦--output.R       
  °--report.R

Now we can run taf.boot to process the script to download the process the zip file and now the directory structure will look like this

taf.boot()
                                                           
 test_datasets                                             
  ¦--boot                                                  
  ¦   ¦--data                                              
  ¦   ¦   °--icesareas                                     
  ¦   ¦       ¦--DISCLAIMER_GIS.txt                        
  ¦   ¦       ¦--ICES_Areas_20160601_cut_dense_3857.cpg    
  ¦   ¦       ¦--ICES_Areas_20160601_cut_dense_3857.dbf    
  ¦   ¦       ¦--ICES_Areas_20160601_cut_dense_3857.prj    
  ¦   ¦       ¦--ICES_Areas_20160601_cut_dense_3857.sbn    
  ¦   ¦       ¦--ICES_Areas_20160601_cut_dense_3857.sbx    
  ¦   ¦       ¦--ICES_Areas_20160601_cut_dense_3857.shp    
  ¦   ¦       ¦--ICES_Areas_20160601_cut_dense_3857.shp.xml
  ¦   ¦       °--ICES_Areas_20160601_cut_dense_3857.shx    
  ¦   ¦--DATA.bib                                          
  ¦   ¦--icesareas.R                                       
  ¦   °--initial                                           
  ¦       °--data                                          
  ¦--data.R                                                
  ¦--model.R                                               
  ¦--output.R                                              
  °--report.R

Get the ICES Word template

We will start with an empty repository

                 
 test_datasets   
  ¦--boot        
  ¦   °--initial 
  ¦       °--data
  ¦--data.R      
  ¦--model.R     
  ¦--output.R    
  °--report.R

To download this file for use in an automated report for a TAF assessment, specify the location of the file as the source of the data record. The file is held in the ices-taf/doc repository and is called reportTemplate.docx. This is done by creating the following meta-data record in DATA.bib

@Misc{reportTemplate.docx,
  originator = {ICES},
  year       = {2023},
  title      = {ICES TAF Word template for report automation},
  access     = {Public},
  source     = {https://github.com/ices-taf/doc/raw/master/reportTemplate.docx},
}

The DATA.bib entry can be created using the draft.data function

  draft.data(
    data.files = "reportTemplate.docx",
    originator = "ICES",
    title = "ICES TAF Word template for report automation",
    period = FALSE,
    source = "https://github.com/ices-taf/doc/raw/master/reportTemplate.docx",
    file = TRUE
  )

The directory structure should now look like this:

                 
 test_datasets   
  ¦--boot        
  ¦   ¦--DATA.bib
  ¦   °--initial 
  ¦       °--data
  ¦--data.R      
  ¦--model.R     
  ¦--output.R    
  °--report.R

Now we can run taf.boot to process the script to download the Word template file and now the directory structure will look like this

taf.boot()
                                
 test_datasets                  
  ¦--boot                       
  ¦   ¦--data                   
  ¦   ¦   °--reportTemplate.docx
  ¦   ¦--DATA.bib               
  ¦   °--initial                
  ¦       °--data               
  ¦--data.R                     
  ¦--model.R                    
  ¦--output.R                   
  °--report.R

Further DATA.bib entries

ICES Statistical Rectangles mapped to Ecoregions

DATA.bib entry:

@Misc{ICES_StatRec_mapto_Ecoregions,
  originator = {DTU Aqua},
  year       = {2019},
  title      = {ICES Stat rec ESRI Shapefile},
  url        = {https://gis.ices.dk/geonetwork/srv/metadata/81f68a99-9b91-4762-80d3-31c069731f44},
  source     = {script},
}

with the R script: ICES_StatRec_mapto_Ecoregions.R

filename <- "ICES_StatRec_mapto_Ecoregions.zip"
# download and unzip
download(paste0("http://gis.ices.dk/shapefiles/", filename))
unzip(filename)
# delete zip file
unlink(filename)

ICES Ecoregion

DATA.bib entry:

@Misc{ICES_ecoregions,
  originator = {ICES},
  year       = {2019},
  title      = {ICES Ecoregion ESRI Shapefile},
  url        = {https://gis.ices.dk/geonetwork/srv/metadata/4745e824-a612-4a1f-bc56-b540772166eb},
  source     = {script},
}

with the R script: ICES_ecoregions.R

filename <- "ICES_ecoregions.zip"
# download and unzip
download(paste0("http://gis.ices.dk/shapefiles/", filename))
unzip(filename)
# delete zip file
unlink(filename)

Species lookup table from ICES SD database

DATA.bib entry:

@Misc{ICES_SD_species_lookup,
  originator = {ICES},
  year       = {2019},
  title      = {ICES Fisheries Guild lookup table},
  url        = {https://gis.ices.dk/geonetwork/srv/metadata/30541cf4-0236-437f-9757-596c5f793cff},
  source     = {script},
}

with the R script: ICES_SD_species_lookup.R

library(icesSD)
library(magrittr)

sid <- getSD()

# get lookup table for species, common name and Fisheries guild from SID
species_lookup <-
  sid %>%
  filter(ActiveYear > 2018) %>%
  select(
    SpeciesScientificName,
    SpeciesCommonName,
    FisheriesGuild
  ) %>%
  mutate(
    FisheriesGuild = tolower(FisheriesGuild)
  ) %>%
  filter(
    !is.na(FisheriesGuild) &
    !is.na(SpeciesScientificName)
  ) %>%
  unique()

write.taf(species_lookup, quote = TRUE)

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