rgbif v0.9.8

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Interface to the Global 'Biodiversity' Information Facility 'API'

A programmatic interface to the Web Service methods provided by the Global Biodiversity Information Facility ('GBIF'; <http://www.gbif.org/developer/summary>). 'GBIF' is a database of species occurrence records from sources all over the globe. 'rgbif' includes functions for searching for taxonomic names, retrieving information on data providers, getting species occurrence records, and getting counts of occurrence records.

Readme

rgbif

Build Status codecov.io rstudio mirror downloads cran version

rgbif gives you access to data from GBIF via their REST API. GBIF versions their API - we are currently using v1 of their API. You can no longer use their old API in this package - see ?rgbif-defunct.

Tutorials:

Package API

The rgbif package API follows the GBIF API, which has the following sections:

  • registry (http://www.gbif.org/developer/registry) - Metadata on datasets, and contributing organizations, installations, networks, and nodes
    • rgbif functions: dataset_metrics(), dataset_search(), dataset_suggest(), datasets(), enumeration(), enumeration_country(), installations(), networks(), nodes(), organizations()
    • Registry also includes the GBIF OAI-PMH service, which includes GBIF registry data only. rgbif functions: gbif_oai_get_records(), gbif_oai_identify(), gbif_oai_list_identifiers(), gbif_oai_list_metadataformats(), gbif_oai_list_records(), gbif_oai_list_sets()
  • species (http://www.gbif.org/developer/species) - Species names and metadata
    • rgbif functions: name_backbone(), name_lookup(), name_suggest(), name_usage()
  • occurrences (http://www.gbif.org/developer/occurrence) - Occurrences, both for the search and download APIs
    • rgbif functions: occ_count(), occ_data(), occ_download(), occ_download_cancel(), occ_download_cancel_staged(), occ_download_get(), occ_download_import(), occ_download_list(), occ_download_meta(), occ_get(), occ_issues(), occ_issues_lookup(), occ_metadata(), occ_search()

The GBIF maps API (http://www.gbif.org/developer/maps) is not implemented in rgbif, and are meant more for intergration with web based maps.

Installation

install.packages("rgbif")

Alternatively, install development version

install.packages("devtools")
devtools::install_github("ropensci/rgbif")
library("rgbif")

Note: Windows users have to first install Rtools to use devtools

Mac Users: (in case of errors)

Terminal:

Install gdal : https://github.com/edzer/sfr/blob/master/README.md#macos

brew install openssl

R terminal:

install.packages('openssl')
install.packages('rgeos')
install.packages('rgbif')

Search for occurrence data

occ_search(scientificName = "Ursus americanus", limit = 50)
#> Records found [8707]
#> Records returned [50]
#> No. unique hierarchies [1]
#> No. media records [28]
#> No. facets [0]
#> Args [limit=50, offset=0, scientificName=Ursus americanus, fields=all]
#> # A tibble: 50 × 68
#>                name        key decimalLatitude decimalLongitude
#>               <chr>      <int>           <dbl>            <dbl>
#> 1  Ursus americanus 1453325042        37.36325        -80.52914
#> 2  Ursus americanus 1453341157        35.44519        -83.75077
#> 3  Ursus americanus 1453341156        35.43836        -83.66423
#> 4  Ursus americanus 1453427952        35.61469        -82.47723
#> 5  Ursus americanus 1453414927        47.90953        -91.95893
#> 6  Ursus americanus 1453456338        25.30959       -100.96966
#> 7  Ursus americanus 1453445710        35.59506        -82.55149
#> 8  Ursus americanus 1453476835        29.24034       -103.30502
#> 9  Ursus americanus 1453456359        25.31110       -100.96992
#> 10 Ursus americanus 1453520782        29.28037       -103.30340
#> # ... with 40 more rows, and 64 more variables: issues <chr>,
#> #   datasetKey <chr>, publishingOrgKey <chr>, publishingCountry <chr>,
#> #   protocol <chr>, lastCrawled <chr>, lastParsed <chr>, crawlId <int>,
#> #   extensions <chr>, basisOfRecord <chr>, taxonKey <int>,
#> #   kingdomKey <int>, phylumKey <int>, classKey <int>, orderKey <int>,
#> #   familyKey <int>, genusKey <int>, speciesKey <int>,
#> #   scientificName <chr>, kingdom <chr>, phylum <chr>, order <chr>,
#> #   family <chr>, genus <chr>, species <chr>, genericName <chr>,
#> #   specificEpithet <chr>, taxonRank <chr>, dateIdentified <chr>,
#> #   coordinateUncertaintyInMeters <dbl>, year <int>, month <int>,
#> #   day <int>, eventDate <chr>, modified <chr>, lastInterpreted <chr>,
#> #   references <chr>, license <chr>, identifiers <chr>, facts <chr>,
#> #   relations <chr>, geodeticDatum <chr>, class <chr>, countryCode <chr>,
#> #   country <chr>, rightsHolder <chr>, identifier <chr>,
#> #   verbatimEventDate <chr>, datasetName <chr>, collectionCode <chr>,
#> #   gbifID <chr>, verbatimLocality <chr>, occurrenceID <chr>,
#> #   taxonID <chr>, catalogNumber <chr>, recordedBy <chr>,
#> #   http...unknown.org.occurrenceDetails <chr>, institutionCode <chr>,
#> #   rights <chr>, eventTime <chr>, occurrenceRemarks <chr>,
#> #   identificationID <chr>, infraspecificEpithet <chr>,
#> #   informationWithheld <chr>

Or you can get the taxon key first with name_backbone(). Here, we select to only return the occurrence data.

key <- name_backbone(name='Helianthus annuus', kingdom='plants')$speciesKey
occ_search(taxonKey=key, limit=20)
#> Records found [9920]
#> Records returned [20]
#> No. unique hierarchies [1]
#> No. media records [4]
#> No. facets [0]
#> Args [limit=20, offset=0, taxonKey=3119195, fields=all]
#> # A tibble: 20 × 76
#>                 name        key decimalLatitude decimalLongitude
#>                <chr>      <int>           <dbl>            <dbl>
#> 1  Helianthus annuus 1433793045        59.66860         16.54260
#> 2  Helianthus annuus 1434024463        63.71620         20.31250
#> 3  Helianthus annuus 1433858538        60.27530         16.88070
#> 4  Helianthus annuus 1453439357        25.66662       -100.25580
#> 5  Helianthus annuus 1436223234        59.85510         17.78900
#> 6  Helianthus annuus 1453443879        24.12030       -110.33479
#> 7  Helianthus annuus 1453421897        33.94156       -117.31729
#> 8  Helianthus annuus 1453463012        25.91457       -100.23617
#> 9  Helianthus annuus 1436147509        59.85470         17.79090
#> 10 Helianthus annuus 1450388036        56.60630         16.64840
#> 11 Helianthus annuus 1455582533        33.73523       -117.39047
#> 12 Helianthus annuus 1453470435        38.68366       -121.17481
#> 13 Helianthus annuus 1433648018        60.83520         15.66670
#> 14 Helianthus annuus 1428322921        59.89010         17.66020
#> 15 Helianthus annuus 1428270308        59.88990         17.66030
#> 16 Helianthus annuus 1249279611        34.04810       -117.79884
#> 17 Helianthus annuus 1428303565        59.89020         17.66080
#> 18 Helianthus annuus 1455567216        34.14489       -117.18974
#> 19 Helianthus annuus 1315048347        34.04377       -116.94136
#> 20 Helianthus annuus 1253308332        29.67463        -95.44804
#> # ... with 72 more variables: issues <chr>, datasetKey <chr>,
#> #   publishingOrgKey <chr>, publishingCountry <chr>, protocol <chr>,
#> #   lastCrawled <chr>, lastParsed <chr>, crawlId <int>, extensions <chr>,
#> #   basisOfRecord <chr>, individualCount <int>, taxonKey <int>,
#> #   kingdomKey <int>, phylumKey <int>, classKey <int>, orderKey <int>,
#> #   familyKey <int>, genusKey <int>, speciesKey <int>,
#> #   scientificName <chr>, kingdom <chr>, phylum <chr>, order <chr>,
#> #   family <chr>, genus <chr>, species <chr>, genericName <chr>,
#> #   specificEpithet <chr>, taxonRank <chr>, coordinatePrecision <dbl>,
#> #   elevation <dbl>, elevationAccuracy <dbl>, depth <dbl>,
#> #   depthAccuracy <dbl>, stateProvince <chr>, year <int>, month <int>,
#> #   day <int>, eventDate <chr>, modified <chr>, lastInterpreted <chr>,
#> #   license <chr>, identifiers <chr>, facts <chr>, relations <chr>,
#> #   geodeticDatum <chr>, class <chr>, countryCode <chr>, country <chr>,
#> #   identifier <chr>, catalogNumber <chr>, institutionCode <chr>,
#> #   locality <chr>, county <chr>, collectionCode <chr>, gbifID <chr>,
#> #   occurrenceID <chr>, identifiedBy <chr>, dateIdentified <chr>,
#> #   coordinateUncertaintyInMeters <dbl>, references <chr>,
#> #   rightsHolder <chr>, verbatimEventDate <chr>, datasetName <chr>,
#> #   verbatimLocality <chr>, taxonID <chr>, recordedBy <chr>,
#> #   http...unknown.org.occurrenceDetails <chr>, rights <chr>,
#> #   eventTime <chr>, identificationID <chr>, occurrenceRemarks <chr>

Search for many species

Get the keys first with name_backbone(), then pass to occ_search()

splist <- c('Accipiter erythronemius', 'Junco hyemalis', 'Aix sponsa')
keys <- sapply(splist, function(x) name_backbone(name=x)$speciesKey, USE.NAMES=FALSE)
occ_search(taxonKey=keys, limit=5, hasCoordinate=TRUE)
#> Occ. found [2480598 (18), 2492010 (3043822), 2498387 (971634)]
#> Occ. returned [2480598 (5), 2492010 (5), 2498387 (5)]
#> No. unique hierarchies [2480598 (1), 2492010 (1), 2498387 (1)]
#> No. media records [2480598 (1), 2492010 (1), 2498387 (1)]
#> No. facets [2480598 (0), 2492010 (0), 2498387 (0)]
#> Args [hasCoordinate=TRUE, limit=5, offset=0,
#>      taxonKey=2480598,2492010,2498387, fields=all]
#> 3 requests; First 10 rows of data from 2480598
#>
#> # A tibble: 5 × 82
#>                      name        key decimalLatitude decimalLongitude
#>                     <chr>      <int>           <dbl>            <dbl>
#> 1 Accipiter erythronemius  920169861      -20.552437        -56.64104
#> 2 Accipiter erythronemius  920184036      -20.760288        -56.71314
#> 3 Accipiter erythronemius 1001096527      -27.580000        -58.66000
#> 4 Accipiter erythronemius 1001096518      -27.920000        -59.14000
#> 5 Accipiter erythronemius  686297260        5.266667        -60.73333
#> # ... with 78 more variables: issues <chr>, datasetKey <chr>,
#> #   publishingOrgKey <chr>, publishingCountry <chr>, protocol <chr>,
#> #   lastCrawled <chr>, lastParsed <chr>, crawlId <int>, extensions <chr>,
#> #   basisOfRecord <chr>, taxonKey <int>, kingdomKey <int>,
#> #   phylumKey <int>, classKey <int>, orderKey <int>, familyKey <int>,
#> #   genusKey <int>, speciesKey <int>, scientificName <chr>, kingdom <chr>,
#> #   phylum <chr>, order <chr>, family <chr>, genus <chr>, species <chr>,
#> #   genericName <chr>, specificEpithet <chr>, taxonRank <chr>,
#> #   coordinateUncertaintyInMeters <dbl>, year <int>, month <int>,
#> #   day <int>, eventDate <chr>, lastInterpreted <chr>, license <chr>,
#> #   identifiers <chr>, facts <chr>, relations <chr>, geodeticDatum <chr>,
#> #   class <chr>, countryCode <chr>, country <chr>, recordedBy <chr>,
#> #   catalogNumber <chr>, institutionCode <chr>, locality <chr>,
#> #   collectionCode <chr>, gbifID <chr>, modified <chr>, identifier <chr>,
#> #   created <chr>, occurrenceID <chr>, associatedSequences <chr>,
#> #   higherClassification <chr>, taxonID <chr>, sex <chr>,
#> #   establishmentMeans <chr>, continent <chr>, references <chr>,
#> #   institutionID <chr>, dynamicProperties <chr>, fieldNumber <chr>,
#> #   language <chr>, type <chr>, preparations <chr>,
#> #   occurrenceStatus <chr>, rights <chr>, higherGeography <chr>,
#> #   verbatimEventDate <chr>, nomenclaturalCode <chr>,
#> #   georeferenceVerificationStatus <chr>, endDayOfYear <chr>,
#> #   datasetName <chr>, verbatimLocality <chr>, otherCatalogNumbers <chr>,
#> #   startDayOfYear <chr>, accessRights <chr>, collectionID <chr>

Maps

Make a simple map of species occurrences.

splist <- c('Cyanocitta stelleri', 'Junco hyemalis', 'Aix sponsa')
keys <- sapply(splist, function(x) name_backbone(name=x)$speciesKey, USE.NAMES=FALSE)
dat <- occ_search(taxonKey=keys, limit=100, return='data', hasCoordinate=TRUE)
library('plyr')
datdf <- ldply(dat)
gbifmap(datdf)

plot of chunk unnamed-chunk-10

Meta

  • Please report any issues or bugs.
  • License: MIT
  • Get citation information for rgbif in R doing citation(package = 'rgbif')
  • Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

This package is part of a richer suite called spocc - Species Occurrence Data, along with several other packages, that provide access to occurrence records from multiple databases.


ropensci_footer

Functions in rgbif

Name Description
count_facet Facetted count occurrence search.
density_spplist The density web service provides access to records showing the density
densitylist The density web service provides access to records showing the density
blanktheme Custom ggplot2 theme
check_wkt Check input WKT
dataset_metrics Get details on a GBIF dataset.
dataset_search Search datasets in GBIF.
dataset_suggest Suggest datasets in GBIF.
datasets Search for datasets and dataset metadata.
downloads Downloads interface
elevation Get elevation for lat/long points from a data.frame or list of points.
gbif_names View highlighted terms in name results from GBIF.
gbif_oai GBIF registry data via OAI-PMH
gbifmap Make a map to visualize GBIF occurrence data.
gbifmap_list Make a simple map to visualize GBIF point data.
get_credentials Get Github credentials from use in console
gbif_photos View photos from GBIF.
gbifdata Get data.frame from occurrencelist, occurrencelist_many, or densitylist.
name_backbone Lookup names in the GBIF backbone taxonomy.
name_lookup Lookup names in all taxonomies in GBIF.
networks Networks metadata.
nodes Nodes metadata.
occ_download_get Get a download from GBIF.
occ_download_import Import a downloaded file from GBIF.
occ_facet Facet GBIF occurrences
occ_download_list Lists the downloads created by a user.
occ_download_meta Retrieves the occurrence download metadata by its unique key.
stylegeojson Style a data.frame prior to converting to geojson.
suggestfields Fields available in gbif_suggest function
gbifmap_dens Make a simple map to visualize GBIF data density data
enumeration Enumerations.
gbif_bbox2wkt Convert a bounding box to a Well Known Text polygon, and a WKT to a
name_suggest A quick and simple autocomplete service that returns up to 20 name
name_usage Lookup details for specific names in all taxonomies in GBIF.
occurrenceget Get individual records for a given occurrence record.
occurrencelist Occurrencelist searches for taxon concept records matching a range of filters.
wkt_parse parse wkt into smaller bits
gist Post a file as a Github gist
installations Installations metadata.
occ_count Get number of occurrence records.
occ_data Search for GBIF occurrences - simplified for speed
occ_fields Vector of fields in the output for the function
occurrencecount Counts taxon concept records matching a range of filters.
occurrencedensity Returns summary counts of occurrence records by one-degree cell for a single
resources Get data resources and their unique keys.
rgb_country_codes Look up 2 character ISO country codes
occ_issues_lookup Lookup occurrence issue definitions and short codes
occ_metadata Search for catalog numbers, collection codes, collector names, and
%>% Pipe operator
providers Get data providers and their unique keys.
create_gist Function that takes a list of files and creates payload for API
gbif_citation Get citation for datasets used
gbif_issues Table of GBIF issues, with codes used in data output, full issue name,
taxoncount Search by taxon to retrieve number of records in GBIF.
taxonget Get taxonomic information on a specific taxon or taxa in GBIF by their taxon
isocodes Table of country two character ISO codes, and GBIF names
many-values Many value inputs to some parameters
occ_download Spin up a download request for GBIF occurrence data.
occ_download_cancel Cancel a download cretion process.
occ_get Get data for specific GBIF occurrences.
occ_issues Parse and examine further GBIF issues on a dataset.
occurrencelist_all Occurrencelist_all carries out an occurrencelist query for a single name and
occurrencelist_many occurrencelist_many is the same as occurrencelist, but takes in a vector
togeojson Convert spatial data files to GeoJSON from various formats.
typestatus Type status options for GBIF searching
taxonsearch Search for taxa in GBIF.
taxrank Get the possible values to be used for (taxonomic) rank arguments in GBIF
occ_search Search for GBIF occurrences
occ_spellcheck Spell check search term for occurrence searches
organizations Organizations metadata.
parsenames Parse taxon names using the GBIF name parser.
rgbif-defunct Defunct functions in rgbif
rgbif-package Interface to the Global Biodiversity Information Facility API.
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License MIT + file LICENSE
URL https://github.com/ropensci/rgbif
BugReports https://github.com/ropensci/rgbif/issues
LazyData true
LazyLoad true
VignetteBuilder knitr
RoxygenNote 6.0.1
NeedsCompilation no
Packaged 2017-04-18 21:13:31 UTC; sacmac
Repository CRAN
Date/Publication 2017-04-18 23:54:33 UTC

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