In parksandwildlife/wastdr: WA Sea Turtle Database 'WAStD' API Wrapper

knitr::opts_chunk$set(collapse = TRUE, comment = "#>", fig.path = "man/figures/README-")

wastdr

The WA Strandings Database WAStD (github) provides a RESTful API. WAStD contains data about turtle strandings, turtle taggings, turtle track and nest encounters, and some ancillary data (areas, surveys, staff). WAStD is accessible to authenticated staff of the WA Department of Biodiversity, Conservation and Attractions. The WAStD API uses token and basic authentication, see vignette on details.

The API returns spatially explicit data as GeoJSON, which can be loaded directly into any standard-compliant GIS environments, e.g. Quantum GIS.

If the data consumer however wishes to analyse data in a statistical package like R, the data need to be transformed from a nested list of lists (GeoJSON properties) into a two-dimensional tabular structure. This requires knowledge about the structure and content of the nested data from WAStD.

The main purpose of wastdr is to facilitate reading, parsing and using WAStD data by providing helpers to access the API and flatten the API outputs into a tidy dplyr::tibble.

The secondary purpose of wastdr is to centralize a collection of commonly used analyses and visualisations of turtle data. As development progresses, example analyses and visualisations will be added to the vignette. Contributions and requests are welcome!

Lastly, to facilitate collaboration with external stakeholders, wastdr contains some anonymised example data (raw GeoJSON and parsed tibble) of turtle taggings, turtle track counts, and turtle nests.

Installation

Install wastdr from GitHub. See also the top level tic.R file for other dependencies.

# install.packages("devtools")
#
# https://github.com/r-spatial/mapview/issues/312
remotes::install_github(
  "r-spatial/mapview",
  dependencies = TRUE,
  upgrade = "always",
  force = TRUE,
  build_vignettes = TRUE
)

remotes::install_github(
  "ropensci/ruODK",
  dependencies = TRUE,
  upgrade = "always",
  force = TRUE,
  build_vignettes = TRUE
)

remotes::install_github(
  "dbca-wa/wastdr",
  dependencies = TRUE,
  upgrade = "always",
  build_vignettes = TRUE
)

While the WAStD API is only accessible to a selected audience, and wastdr is under active development, it is not feasible to release wastdr on CRAN yet. Therefore, wastdr will be distributed via GitHub for the time being.

Setup

wastdr requires to be configured with the WAStD API URL and an access token or a username / password combination. wastdr functions expect these settings to be available as environment variables. For convenience, wastdr_setup sets the correct variables, while wastdr_settings retrieves the currently set values.

DBCA staff can find their WAStD API Token at WAStD under "My Profile" and add to their .Renviron. To use ODK Central turtle data download helpers, also add ODK Central credentials.

WASTDR_API_URL <- "https://wastd.dbca.wa.gov.au/api/1/"
WASTDR_API_TOKEN <- "Token XXX"
WASTDR_VERBOSE <- TRUE

ODKC_URL <- "https://odkcentral.dbca.wa.gov.au"
ODKC_UN <- "..."
ODKC_PW <- "..."

External collaborators can use their allocated WAStD username and password:

WASTDR_API_URL <- "https://wastd.dbca.wa.gov.au/api/1/"
WASTDR_API_UN <- "..."
WASTDR_API_PW <- "..."
WASTDR_VERBOSE <- TRUE

ODKC_URL <- "https://odkcentral.dbca.wa.gov.au"
ODKC_UN <- "..."
ODKC_PW <- "..."

Review the settings with:

wastdr::wastdr_settings()

For other configuration methods please see the vignette "Setup".

Get WAStD

Once set up, wastdr can load data from WAStD simply with:

tracks <- "turtle-nest-encounters" %>%
  wastd_GET(max_records = 10) %>%
  parse_turtle_nest_encounters()

Valid endpoints are listed in the base API URL of WAStD, e.g.:

encounters
animal-encounters
turtle-nest-encounters
turte-nest-disturbance-observations

...or have a pickle

If you don't have access to the WAStD API, you can still get a feel for the data by using the pickled example data:

library(wastdr)

data("wastd_data")
data("odkc_data")

wastd_data

wastd_data$animals
wastd_data$tracks

wastd_data$tracks %>% map_tracks(sites = wastd_data$sites)
odkc_data$tracks %>% map_tracks_odkc(sites = odkc_data$sites)

Learn more

See the vignettes for built-in helpers to transform, analyse and visualize WAStD data.

vignette("getting-wastd", package = "wastdr")
vignette("analysis", package = "wastdr")

Contribute

Every contribution, constructive feedback, or suggestion is welcome!

Send us your ideas and requests as issues or submit a pull request.

Pull requests should eventually pass tests and checks (not introducing new ERRORs, WARNINGs or NOTEs apart from the "New CRAN package" NOTE):

styler:::style_pkg()
spelling::spell_check_package()
spelling::update_wordlist()
devtools::document(roclets = c("rd", "collate", "namespace", "vignette"))
devtools::build()
devtools::test()
devtools::check(force_suggests = T, args = c("--as-cran", "--timings"))
rcmdcheck::rcmdcheck()
goodpractice::goodpractice(quiet = F)
covr::codecov(token = Sys.getenv("CODECOV_TOKEN"))
usethis::use_version("patch")