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galah is an R interface to biodiversity data hosted by the Atlas of Living Australia (ALA). It 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 data.tree package.

The ALA is an aggregator of biodiversity data, focussed primarily on observations of individual life forms. Like the Global Biodiversity Information Facility (GBIF), the basic unit of data at ALA is an occurrence record, based on the ‘Darwin Core’ data standard.

The galah 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.

Getting started


Install from CRAN:


Install the development version from GitHub:


On Linux you will first need to ensure that libcurl and 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 atlas_citation().

# Download occurrence records with a DOI 
occ <- atlas_occurrences(..., mint_doi = TRUE)

# See DOI
attr(occ, "doi")

# Generate citation