corella

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.

If you have any questions, comments, or spot any bugs, email us or report an issue in the R package or the Python package on our GitHub page.

library(corella)

# example data
my_data <- tibble::tibble(
  latitude = c(-35.310, -35.273),
  longitude = c(149.125, 149.133),
  species = c("Callocephalon fimbriatum", "Eolophus roseicapilla"),
  location_id = c("ARD001", "ARD001")
  )

# standardise
my_data |>
  set_occurrences(
    occurrenceID = composite_id(location_id, sequential_id()),
    basisOfRecord = "humanObservation"
    ) |> 
  set_coordinates(
    decimalLatitude = latitude, 
    decimalLongitude = longitude
    ) |>
  set_locality(
    country = "Australia", 
    locality = "Canberra"
    ) |>
  set_scientific_name(
    scientificName = species, 
    taxonRank = "species"
    ) |>
  set_taxonomy(
    kingdom = "Animalia", 
    phylum = "Aves"
    )

# A tibble: 2 × 11
  location_id occurrenceID basisOfRecord    decimalLatitude decimalLongitude
  <chr>       <chr>        <chr>                      <dbl>            <dbl>
1 ARD001      ARD001-01    humanObservation           -35.3             149.
2 ARD001      ARD001-02    humanObservation           -35.3             149.
# ℹ 6 more variables: country <chr>, locality <chr>, scientificName <chr>,
#   taxonRank <chr>, kingdom <chr>, phylum <chr>

import pandas as pd
import corella

# example data
my_data = pd.DataFrame({
  "latitude" : [-35.310, -35.273],
  "longitude": [149.125, 149.133],
  "species": ["Callocephalon fimbriatum", "Eolophus roseicapilla"],
  "location_id": ["ARD001", "ARD001"]
})

# standardise
my_data = corella.set_occurrences(
  my_data,
  occurrenceID = True,composite_id="location_id",sequential_id=True,add_sequential_id='first',
  basisOfRecord = "HumanObservation"
)
my_data = corella.set_coordinates(
  my_data,
  decimalLatitude = "latitude",
  decimalLongitude = "longitude"
)
my_data = corella.set_locality(
  my_data,
  country = "Australia",
  locality = "Canberra"
)
my_data = corella.set_scientific_name(
  my_data,
  scientificName = "species",
  taxonRank = "species"
)
my_data = corella.set_taxonomy(
  my_data,
  kingdom = "Animalia",
  phylum = "Aves"
)
my_data

  occurrenceID  decimalLatitude  decimalLongitude  ...  locality   kingdom phylum
0     0-ARD001          -35.310           149.125  ...  Canberra  Animalia   Aves
1     1-ARD001          -35.273           149.133  ...  Canberra  Animalia   Aves

[2 rows x 10 columns]