beastr

Better Environment/Animal Sensor Telemetry Repository

“Better” as in “better than nothing”. There are many other solutions that are more developed than this, most notably Movebank. Also I’m just really bad at naming things.

The goal of beastr is to provide a framework for storing, accessing, and processing wildlife telemetry data.

Installation

You can install the package using the devtools package

devtools::install_github('rgzn/beastr')

Details

For more details see the articles/vignettes on this package. In particular, the Introduction will explain what data this deals with and why.

Example

Build your database:

library(beastr, quietly = TRUE)
library(sf, quietly = TRUE)

# Use example source data
fix_file = system.file("lotek/PinPoint33452.txt", package = "beastr")
device_file = system.file("devices/collars.csv", package = "beastr")
animal_file = system.file("animals/critters.csv", package = "beastr")
deploy_file = system.file("deployments/deployments.csv", package = "beastr")
myDB = paste0(tempdir(check = TRUE), "/", "example.gpkg")

# Build a database
build_database(fix_files = fix_file,
               device_files = device_file,
               animal_files = animal_file,
               deployment_files = deploy_file,
               dsn = myDB,
               tz = "US/Pacific")

# What layers are in there?
sf::st_layers(myDB)
#> Driver: GPKG 
#> Available layers:
#>     layer_name geometry_type features fields crs_name
#> 1        fixes         Point      468     14    32611
#> 2 animal_fixes         Point      462     12    32611
#> 3      devices            NA       33      7     <NA>
#> 4      animals            NA        4      5     <NA>
#> 5  deployments            NA       20      6     <NA>

View data linked to animals, rather than sensors:

library(dplyr, quietly = TRUE)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(ggplot2, quietly = TRUE)

points = sf::st_read(myDB, layer = "animal_fixes")
#> Reading layer `animal_fixes' from data source 
#>   `/private/var/folders/q2/53ffh3110_5fqqp7tmq2s5th0000gn/T/Rtmp3rOe53/example.gpkg' 
#>   using driver `GPKG'
#> Simple feature collection with 462 features and 12 fields (with 160 geometries empty)
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: 261780.2 ymin: 4173114 xmax: 267257.4 ymax: 4178607
#> CRS:           32611

points %>% 
  ggplot2::ggplot() + 
  ggplot2::geom_sf(ggplot2::aes(fill = animal_id))

Related Projects

• ctmmweb [https://github.com/ctmm-initiative/ctmmweb]
• collardb [https://github.com/kissmygritts/collardb]
• amt [https://github.com/jmsigner/amt]
• movebank [https://www.movebank.org/]

TODO

• integrate with {amt} (use amt tools)
• integrate with movebank (export/import)
• add new readers as new devices are used
• use {golem} for the shiny app stuff