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CoordinateCleaner

Automated flagging of common spatial and temporal errors in biological and palaeontological collection data, for the use in conservation, ecology and palaeontology.
https://github.com/ropensci/coordinatecleaner

Category: Biosphere
Sub Category: Biodiversity Data Cleaning and Standardization

Keywords

r r-package rstats

Keywords from Contributors

biodiversity gbif spocc ecology spatial-analysis gdal geo openscience hugo genome

Last synced: about 14 hours ago
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Automated flagging of common spatial and temporal errors in biological and palaeontological collection data, for the use in conservation, ecology and palaeontology.

README.md

CoordinateCleaner v3.0

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Project Status: Active – The project has reached a stable, usable state and is being actively developed.
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CoordinateCleaner has been updated to version 3.0 on github and on CRAN to adapt to the retirement of sp and raster. The update may not be compatible with analysis-pipelines build with version 2.x*

Automated flagging of common spatial and temporal errors in biological and palaeontological collection data, for the use in conservation, ecology and palaeontology. Specifically includes tests for

  • General coordinate validity
  • Country and province centroids
  • Capital coordinates
  • Coordinates of biodiversity institutions
  • Spatial outliers
  • Temporal outliers
  • Coordinate-country discordance
  • Duplicated coordinates per species
  • Assignment to the location of the GBIF headquarters
  • Urban areas
  • Seas
  • Plain zeros
  • Equal longitude and latitude
  • Rounded coordinates
  • DDMM to DD.DD coordinate conversion errors
  • Large temporal uncertainty (fossils)
  • Equal minimum and maximum ages (fossils)
  • Spatio-temporal outliers (fossils)

CoordinateCleaner can be particularly useful to improve data quality when using data from GBIF (e.g. obtained with rgbif) or the Paleobiology database (e.g. obtained with paleobioDB) for historical biogeography (e.g. with BioGeoBEARS or phytools), automated conservation assessment (e.g. with speciesgeocodeR or conR) or species distribution modelling (e.g. with dismo or sdm). See scrubr and taxize for complementary taxonomic cleaning or biogeo for correcting spatial coordinate errors.

See News for update information.

Installation

Stable from CRAN

install.packages("CoordinateCleaner")
library(CoordinateCleaner)

Developmental from GitHub

devtools::install_github("ropensci/CoordinateCleaner")
library(CoordinateCleaner)

Usage

A simple example:

# Simulate example data
minages <- runif(250, 0, 65)
exmpl <- data.frame(species = sample(letters, size = 250, replace = TRUE),
                    decimalLongitude = runif(250, min = 42, max = 51),
                    decimalLatitude = runif(250, min = -26, max = -11),
                    min_ma = minages,
                    max_ma = minages + runif(250, 0.1, 65),
                    dataset = "clean")

# Run record-level tests
rl <- clean_coordinates(x = exmpl)
summary(rl)
plot(rl)

# Dataset level 
dsl <- clean_dataset(exmpl)

# For fossils
fl <- clean_fossils(x = exmpl,
                          taxon = "species",
                          lon = "decimalLongitude", 
                          lat = "decimalLatitude")
summary(fl)

# Alternative example using the pipe
library(tidyverse)

cl <- exmpl %>%
  cc_val()%>%
  cc_cap()%>%
  cd_ddmm()%>%
  cf_range(lon = "decimalLongitude", 
           lat = "decimalLatitude", 
           taxon  ="species")

Documentation

Pipelines for cleaning data from the Global Biodiversity Information Facility (GBIF) and the Paleobiology Database (PaleobioDB) are available in here.

Contributing

See the CONTRIBUTING document.

Citation

Zizka A, Silvestro D, Andermann T, Azevedo J, Duarte Ritter C, Edler D, Farooq H, Herdean A, Ariza M, Scharn R, Svanteson S, Wengtrom N, Zizka V & Antonelli A (2019) CoordinateCleaner: standardized cleaning of occurrence records from biological collection databases. Methods in Ecology and Evolution, 10(5):744-751, doi:10.1111/2041-210X.13152, https://github.com/ropensci/CoordinateCleaner

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Last synced: 5 days ago

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Commits in past year: 33
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Name Email Commits
azizka a****a@b****e 394
azizka z****r@g****m 187
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Pakillo f****c@g****m 28
Irene j****e@e****m 20
Maëlle Salmon m****n@y****e 4
Hugo Gruson B****o 2
Jeroen Ooms j****s@g****m 2
mhesselbarth m****h@g****m 2
John Baumgartner j****s@g****m 1
John Waller f****2@s****n 1
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Vince Buffalo v****A@g****m 1
AMBarbosa A****a 1
Michael Sumner m****r@g****m 1

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Package metadata

cran.r-project.org: CoordinateCleaner

Automated Cleaning of Occurrence Records from Biological Collections

  • Homepage: https://ropensci.github.io/CoordinateCleaner/
  • Documentation: http://cran.r-project.org/web/packages/CoordinateCleaner/CoordinateCleaner.pdf
  • Licenses: GPL-3
  • Latest release: 3.0.1 (published over 1 year ago)
  • Last Synced: 2025-04-25T12:08:08.976Z (1 day ago)
  • Versions: 15
  • Dependent Packages: 5
  • Dependent Repositories: 7
  • Downloads: 1,324 Last month
  • Rankings:
    • Forks count: 3.648%
    • Stargazers count: 5.337%
    • Average: 8.638%
    • Dependent packages count: 10.686%
    • Dependent repos count: 11.271%
    • Downloads: 12.247%
  • Maintainers (1)

Dependencies

DESCRIPTION cran
  • R >= 3.5.0 depends
  • dplyr * imports
  • geosphere * imports
  • ggplot2 * imports
  • grDevices * imports
  • graphics * imports
  • methods * imports
  • raster * imports
  • rgbif * imports
  • rgdal * imports
  • rgeos * imports
  • rnaturalearth * imports
  • sp * imports
  • stats * imports
  • tidyselect * imports
  • utils * imports
  • countrycode * suggests
  • covr * suggests
  • knitr * suggests
  • magrittr * suggests
  • maps * suggests
  • paleobioDB * suggests
  • rmarkdown * suggests
  • rnaturalearthdata * suggests
  • testthat * suggests
  • viridis * suggests
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  • r-lib/actions/setup-pandoc v1 composite
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  • r-lib/actions/setup-r-dependencies v1 composite
.github/workflows/pkgdown.yaml actions
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  • r-lib/actions/setup-pandoc v1 composite
  • r-lib/actions/setup-r v1 composite
  • r-lib/actions/setup-r-dependencies v1 composite

Score: 14.64360113380363