galah is an R interface to biodiversity data hosted by the ‘living atlases’; a set of organisations that share a common codebase, and act as nodes of the Global Biodiversity Information Facility (GBIF). These organisations collate and store observations of individual life forms, using the ‘Darwin Core’ data standard.
galah was built and is maintained by the Science & Decision Support Team at the Atlas of Living Australia (ALA).
galah enables users to locate and download species occurrence records (observations, specimens, eDNA records, etc.), taxonomic information, or associated media such as images or sounds, and to restrict their queries to particular taxa or locations. Users can specify which columns are returned by a query, or restrict their results to occurrences that meet particular data-quality criteria. All functions return a
tibble as their standard format, except
atlas_taxonomy which returns tree consisting of
Node objects using the
The package is named for the bird of the same name (Eolophus roseicapilla), a widely-distributed endemic Australian species. The logo was designed by Ian Brennan.
If you have any comments, questions or suggestions, please contact us.
- The quick start guide provides an introduction to the package functions.
- For an outline of the package structure, and a list of all the available functions, run
?galahor view the reference page.
Install from CRAN:
Install the development version from GitHub:
On Linux you will first need to ensure that
v8 (version <= 3.15) are installed on your system — e.g. on Ubuntu/Debian, open a terminal and do:
sudo apt-get install libcurl4-openssl-dev libv8-3.14-dev
galah depends on
sf for location-based searches. To install
galah you will need to make sure your system meets the
sf system requirements, as specified here
To generate a citation for the package version you are using, you can run
citation(package = "galah")
If you’re using occurrence data downloaded through
galah in a publication, please generate a DOI and cite it. To request a DOI for a download of occurrence record, set
mint_doi = TRUE in a call to
atlas_occurrences(). To generate a citation for the downloaded occurrence records, pass the
data.frame generated to
# Download occurrence records with a DOI occ <- atlas_occurrences(..., mint_doi = TRUE) # See DOI attr(occ, "doi") # Generate citation atlas_citation(occ)