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The most common form of data stored by ALA are observations of individual life forms, known as 'occurrences'. This function allows the user to search for occurrence records that match their specific criteria, and return them as a data.frame for analysis. Optionally, the user can also request a DOI for a given download to facilitate citation and re-use of specific data resources.


  request = NULL,
  identify = NULL,
  filter = NULL,
  geolocate = NULL,
  select = galah_select(group = "basic"),
  mint_doi = FALSE,
  doi = NULL,
  refresh_cache = FALSE



optional data_rquest object: generated by a call to galah_call().


data.frame: generated by a call to galah_identify().


data.frame: generated by a call to galah_filter()


string: generated by a call to galah_geolocate()


data.frame: generated by a call to galah_select()


logical: by default no DOI will be generated. Set to TRUE if you intend to use the data in a publication or similar


string: this argument enables retrieval of occurrence records previously downloaded from the ALA, using the DOI generated by the data.


logical: if set to TRUE and galah_config(caching = TRUE) then files cached from a previous query will be replaced by the current query


An object of class tbl_df and data.frame (aka a tibble) of occurrences, containing columns as specified by galah_select(). The data.frame object has the following attributes:

  • a listing of the user-supplied arguments of the data_request (i.e., identify, filter, geolocate, select)

  • a doi of the data download

  • the search_url of the query to ALA API


Note that unless care is taken, some queries can be particularly large. While most cases this will simply take a long time to process, if the number of requested records is >50 million the call will not return any data. Users can test whether this threshold will be reached by first calling atlas_counts() using the same arguments that they intend to pass to atlas_occurrences(). It may also be beneficial when requesting a large number of records to show a progress bar by setting verbose = TRUE in galah_config().


Search for occurrences matching a taxon identifier

galah_config(email = "")
galah_call() |>
  galah_identify("Reptilia") |>

Search for occurrences in a year range

galah_call() |>
  galah_filter(year >= 2010, year <= 2020) |>

Search for occurrences in a WKT-specified area

polygon <- "POLYGON((146.24960 -34.05930,146.37045 -34.05930,146.37045 -34.152549,146.24960 -34.15254,146.24960 -34.05930))"
galah_call() |> 
  galah_geolocate(polygon) |>

You can also download occurrence records by piping with %>% if you prefer.

galah_call() %>%
  galah_identify("Reptilia") %>%
  galah_filter(year >= 2010) %>%
  galah_geolocate(polygon) %>%