Overview
corella is an R package that helps users standardize their data using the Darwin Core data standard, used for biodiversity data like species occurrences. corella provides tools to prepare, manipulate and validate data against the standard’s criteria. Once standardized, data can be subsequently shared as a Darwin Core Archive and published to open data infrastructures like the Atlas of Living Australia and GBIF.
corella was built, and is maintained, by the Science & Decision Support Team at the Atlas of Living Australia (ALA). It is named for the Little Corella (Cacatua sanguinea). The logo was designed by Dax Kellie.
If you have any comments, questions or suggestions, please contact us.
Installation
Install from CRAN:
install.packages("corella")Install the development version of corella from GitHub:
# install.packages("devtools")
devtools::install_github("AtlasOfLivingAustralia/corella")Usage
Here we have a small sample of example data containing observations of cockatoos. Using corella we can convert our data to use Darwin Core Standard.
library(corella)
library(tibble)
# A simple example of species occurrence data
df <- tibble(
species = c("Callocephalon fimbriatum", "Eolophus roseicapilla"),
latitude = c(-35.310, "-35.273"), # deliberate error for demonstration purposes
longitude = c(149.125, 149.133),
eventDate = c("14-01-2023", "15-01-2023"),
status = c("present", "present")
)
df
#> # A tibble: 2 × 5
#> species latitude longitude eventDate status
#> <chr> <chr> <dbl> <chr> <chr>
#> 1 Callocephalon fimbriatum -35.31 149. 14-01-2023 present
#> 2 Eolophus roseicapilla -35.273 149. 15-01-2023 presentOne of the most important aspects of Darwin Core Standard is using standard column names (Darwin Core terms). We can update column names in our data to match Darwin Core terms with set_ functions.
Each set_ function name corresponds to the type of data, and argument names correspond to the available Darwin Core terms to use as column names. set_ functions support data wrangling operations & dplyr::mutate() functionality, meaning columns can be changed or fixed in your pipe. set_ functions will indicate if anything needs fixing because they also automatically run checks on each column data to make sure each column is in the correct format.
suppressMessages( # for readability
df |>
set_coordinates(
decimalLatitude = as.numeric(latitude), # fix latitude
decimalLongitude = longitude
) |>
set_scientific_name(
scientificName = species
) |>
set_datetime(
eventDate = lubridate::dmy(eventDate) # specify date format
) |>
set_occurrences(occurrenceStatus = status)
)
#> # A tibble: 2 × 5
#> eventDate decimalLatitude decimalLongitude scientificName occurrenceStatus
#> <date> <dbl> <dbl> <chr> <chr>
#> 1 2023-01-14 -35.3 149. Callocephalon fi… present
#> 2 2023-01-15 -35.3 149. Eolophus roseica… presentNot sure where to start? Use suggest_workflow() to know what steps you need to make to make your data Darwin Core compliant.
df |>
suggest_workflow()
#>
#> ── Matching Darwin Core terms ──────────────────────────────────────────────────
#> Matched 1 of 5 column names to DwC terms:
#> ✔ Matched: eventDate
#> ✖ Unmatched: latitude, longitude, species, status
#>
#> ── Minimum required Darwin Core terms ──────────────────────────────────────────
#>
#> Type Matched term(s) Missing term(s)
#> ✔ Date/Time eventDate -
#> ✖ Identifier (at least one) - occurrenceID, catalogNumber, recordNumber
#> ✖ Record type - basisOfRecord
#> ✖ Scientific name - scientificName
#> ✖ Location - decimalLatitude, decimalLongitude, geodeticDatum, coordinateUncertaintyInMeters
#>
#> ── Suggested workflow ──────────────────────────────────────────────────────────
#>
#> To make your data Darwin Core compliant, use the following workflow:
#> df |>
#> set_occurrences() |>
#> set_coordinates() |>
#> set_scientific_name()
#>
#> ── Additional functions
#> ℹ See all `set_` functions at
#> http://corella.ala.org.au/reference/index.html#add-rename-or-edit-columns-to-match-darwin-core-termsOr, if your data is nearly ready and you want to run checks over all columns that match Darwin Core terms, run check_dataset().
df |>
check_dataset()
#> ℹ Testing data
#> ✔ | E P | Column
#> ⠙ | 0 eventDate
#> ⠹ | 1 ✖ | eventDate ✔ | 1 ✖ | eventDate [111ms]
#> ══ Results ═════════════════════════════════════════════════════════════════════
#>
#> [ Errors: 1 | Pass: 0 ]
#> ℹ Checking Darwin Core compliance
#> ✖ Data does not meet minimum Darwin Core column requirements
#> ℹ Use `suggest_workflow()` to see more information.
#> ── Error in term ───────────────────────────────────────────────────────────────
#>
#> eventDate must be a Date vector, not a character.
#> ℹ Specify date format with lubridate functions e.g. `ymd()`, `mdy()`, or
#> `dmy()`.Citing corella
To generate a citation for the package version you are using, you can run:
citation(package = "corella")The current recommended citation is:
Kellie D, Balasubramaniam S & Westgate MJ (2025) corella: Tools to standardize biodiversity data to Darwin Core. R Package version 0.1.4.