rvertnet
is a client for interacting with VertNet.org.
Stable CRAN version
install.packages("rvertnet")
Development version from GitHub
remotes::install_github("ropensci/rvertnet", build_vignettes = TRUE)
library('rvertnet')
Search for Aves in the state of California, limit to 10 records
res <- searchbyterm(class = "Aves", state = "California", limit = 10, messages = FALSE)
All major functions (searchbyterm()
, spatialsearch()
, vertsearch()
) give back a meta
(for metadata, in a list) and data
(for data, in a data.frame) slot. The metadata:
res$meta #> $request_date #> [1] "2024-02-15T03:20:26.162111" #> #> $response_records #> [1] 10 #> #> $submitted_query #> [1] "class:Aves" #> #> $request_origin #> [1] "47.252877,-122.444291" #> #> $limit #> [1] 10 #> #> $last_cursor #> [1] "False:CskFCtIDCqQD9wAAABn_____jIGJmo2LkZqL0o-QjYuek96WkZuah9LNz87M0s_H0s_H_wAA_3RtoKCZi4ygoP8AAP9dno-PmpGYlpGa_wAA_3N0bZaRm5qH_wAA_12biJz_AAD_c3Rtm5CcoJab_wAA_12ektCQjZGWi5eQk5CYhtDPz87GmcjGztLGzcbJ0svPzprSxsfGy9Kdycqcz53NnMfGnpv_AAD_c3-ektCQjZGWi5eQk5CYhtDPz87GmcjGztLGzcbJ0svPzprSxsfGy9Kdycqcz53NnMfGnpv_AAD__wD-__6MgYmajYuRmovSj5CNi56T3paRm5qH0s3PzszSz8fSz8f_AHRtoKCZi4ygoP8AXZ6Pj5qRmJaRmv8Ac3RtlpGbmof_AF2biJz_AHN0bZuQnKCWm_8AXZ6S0JCNkZaLl5CTkJiG0M_PzsaZyMbO0sbNxsnSy8_OmtLGx8bL0p3JypzPnc2cx8aem_8Ac3-ektCQjZGWi5eQk5CYhtDPz87GmcjGztLGzcbJ0svPzprSxsfGy9Kdycqcz53NnMfGnpv_AP_-EAohBN0EkB08Gxk5AAAAAOb___9IClAAWgsJJ5Q__S_keXEQA2D6k__lBRINRG9jdW1lbnRJbmRleBrAAShBTkQgKElTICJjdXN0b21lcl9uYW1lIiAiYXBwZW5naW5lIikgKElTICJncm91cF9uYW1lIiAic352ZXJ0bmV0LXBvcnRhbCIpIChJUyAibmFtZXNwYWNlIiAiaW5kZXgtMjAxMy0wOC0wOCIpIChJUyAiaW5kZXhfbmFtZSIgImR3YyIpIChPUiAoUVQgIkF2ZXMiICJydGV4dF9jbGFzcyIpIChJUyAicmF0b21fY2xhc3MiICJhdmVzIikpKToZCgwoTiBvcmRlcl9pZCkQARkAAAAAAADw_0oFCABA6Ac" #> #> $query_version #> [1] "search.py 2016-08-15T16:43+02:00" #> #> $matching_records #> [1] ">10000" #> #> $api_version #> [1] "api.py 2017-11-24T12:16-03:00"
Inspect data. A tibble
is returned, so you get a nice brief data summary:
res$data #> # A tibble: 10 × 46 #> kingdom recordedby higherclassification stateprovince basisofrecord month #> <chr> <chr> <chr> <chr> <chr> <chr> #> 1 Animalia NSW STATE GO… Animalia | Chordata… New South Wa… PreservedSpe… 11 #> 2 Animalia TARONGA ZOO … Animalia | Chordata… New South Wa… PreservedSpe… 6 #> 3 Animalia MCLENNAN, MR… Animalia | Chordata… Queensland PreservedSpe… 4 #> 4 Animalia WATTS, MIKE Animalia | Chordata… New South Wa… PreservedSpe… 1 #> 5 Animalia HOLCOMBE, B. Animalia | Chordata… New South Wa… PreservedSpe… 7 #> 6 Animalia RHODES, C. A. Animalia | Chordata… New South Wa… PreservedSpe… 10 #> 7 Animalia C. HEDLEY, A… Animalia | Chordata… Queensland PreservedSpe… 10 #> 8 Animalia ROBINSON, SEP Animalia | Chordata… New South Wa… PreservedSpe… 10 #> 9 Animalia SHARP, GEORGE Animalia | Chordata… Queensland PreservedSpe… 11 #> 10 Animalia J.A. KEAST, … Animalia | Chordata… New South Wa… PreservedSpe… 3 #> # ℹ 40 more variables: decimallongitude <chr>, phylum <chr>, references <chr>, #> # year <chr>, startdayofyear <chr>, taxonrank <chr>, specificepithet <chr>, #> # bibliographiccitation <chr>, family <chr>, countrycode <chr>, #> # geodeticdatum <chr>, coordinateuncertaintyinmeters <chr>, #> # highergeography <chr>, accessrights <chr>, verbatimlocality <chr>, #> # verbatimeventdate <chr>, day <chr>, eventid <chr>, collectioncode <chr>, #> # occurrencestatus <chr>, locationremarks <chr>, coordinateprecision <chr>, …
Search for Mustela nigripes in the states of Wyoming or South Dakota, limit to 20 records
res <- searchbyterm(specificepithet = "nigripes", genus = "Mustela", state = "(wyoming OR south dakota)", limit = 20, messages = FALSE) res$data #> # A tibble: 20 × 76 #> month decimallongitude startdayofyear accessrights kingdom #> <chr> <chr> <chr> <chr> <chr> #> 1 1 -88.305352 1 http://vertnet.org/resources/n… Animal… #> 2 03 -104.77472 74 http://vertnet.org/resources/n… Animal… #> 3 02 -103.731861 52 http://vertnet.org/resources/n… Animal… #> 4 12 -105.0137067407 349 http://vertnet.org/resources/n… Animal… #> 5 2 -103.067931 32 http://vertnet.org/resources/n… Animal… #> 6 1 -103.067931 1 http://vertnet.org/resources/n… Animal… #> 7 02 -103.067931 40 http://vertnet.org/resources/n… Animal… #> 8 05 -104.926320116 126 http://vertnet.org/resources/n… Animal… #> 9 02 -104.79742 42 http://vertnet.org/resources/n… Animal… #> 10 04 -106.1329632593 108 http://vertnet.org/resources/n… Animal… #> 11 10 -105.064706 304 http://vertnet.org/resources/n… Animal… #> 12 4 -106.3467709375 92 http://vertnet.org/resources/n… Animal… #> 13 05 -104.225829 133 http://vertnet.org/resources/n… Animal… #> 14 09 -105.873904 258 http://vertnet.org/resources/n… Animal… #> 15 12 -105.298898 362 http://vertnet.org/resources/n… Animal… #> 16 06 -105.376986 152 http://vertnet.org/resources/n… Animal… #> 17 11 -104.3831505257 305 http://vertnet.org/resources/n… Animal… #> 18 11 -104.7714765 314 http://vertnet.org/resources/n… Animal… #> 19 09 -106.9094 267 http://vertnet.org/resources/n… Animal… #> 20 08 -107.5579841 234 http://vertnet.org/resources/n… Animal… #> # ℹ 71 more variables: verbatimcoordinatesystem <chr>, day <chr>, #> # identificationverificationstatus <chr>, occurrenceid <chr>, #> # identificationqualifier <chr>, georeferenceddate <chr>, #> # verbatimeventdate <chr>, coordinateuncertaintyinmeters <chr>, #> # higherclassification <chr>, sex <chr>, year <chr>, specificepithet <chr>, #> # basisofrecord <chr>, geodeticdatum <chr>, occurrenceremarks <chr>, #> # highergeography <chr>, continent <chr>, scientificname <chr>, …
Search for class Aves, in the state of Nevada, with a coordinate uncertainty range (in meters) of less than 25 meters
res <- searchbyterm(class = "Aves", stateprovince = "Nevada", error = "<25", messages = FALSE) res$data #> # A tibble: 1,000 × 91 #> georeferenceprotocol higherclassification stateprovince lifestage month #> <chr> <chr> <chr> <chr> <chr> #> 1 MaNIS/HerpNet/ORNIS Geore… Animalia; Chordata;… Nevada U-Ad. 3 #> 2 MaNIS/HerpNet/ORNIS Geore… Animalia; Chordata;… Nevada U-Ad 12 #> 3 MaNIS/HerpNet/ORNIS Geore… Animalia; Chordata;… Nevada Nestling 5 #> 4 MaNIS/HerpNet/ORNIS Geore… Animalia; Chordata;… Nevada U-Ad. 9 #> 5 MaNIS/HerpNet/ORNIS Geore… Animalia; Chordata;… Nevada U-Ad. 9 #> 6 MaNIS/HerpNet/ORNIS Geore… Animalia; Chordata;… Nevada U-Ad. 9 #> 7 MaNIS/HerpNet/ORNIS Geore… Animalia; Chordata;… Nevada Downy 6 #> 8 MaNIS/HerpNet/ORNIS Geore… Animalia; Chordata;… Nevada U-Ad. 6 #> 9 MaNIS/HerpNet/ORNIS Geore… Animalia; Chordata;… Nevada U-Ad. 6 #> 10 MaNIS/HerpNet/ORNIS Geore… Animalia; Chordata;… Nevada U-Ad. 6 #> # ℹ 990 more rows #> # ℹ 86 more variables: decimallongitude <chr>, phylum <chr>, #> # verbatimlongitude <chr>, year <chr>, specificepithet <chr>, #> # bibliographiccitation <chr>, verbatimlatitude <chr>, family <chr>, #> # locality <chr>, geodeticdatum <chr>, coordinateuncertaintyinmeters <chr>, #> # highergeography <chr>, continent <chr>, scientificnameauthorship <chr>, #> # day <chr>, kingdom <chr>, institutioncode <chr>, scientificname <chr>, …
You can pass the data object directly on to dplyr
functions. Here, we get a table of record counts by species in descending order.
library("dplyr") out <- searchbyterm(genus = "Ochotona", limit = 800) out$data %>% group_by(scientificname) %>% summarise(count = length(scientificname)) %>% arrange(desc(count)) #> # A tibble: 20 × 2 #> scientificname count #> <chr> <int> #> 1 Ochotona princeps 450 #> 2 Ochotona pallasi 129 #> 3 Ochotona princeps saxatilis 103 #> 4 Ochotona hyperborea 30 #> 5 Ochotona dauurica 21 #> 6 Ochotona collaris 15 #> 7 Ochotona princeps figginsi 14 #> 8 Ochotona princeps taylori 8 #> 9 Ochotona princeps schisticeps 6 #> 10 Ochotona alpina 4 #> 11 Ochotona princeps muiri 4 #> 12 Ochotona hyperborea mantchurica 3 #> 13 Ochotona princeps incana 3 #> 14 Ochotona princeps princeps 3 #> 15 Ochotona princeps murri 2 #> 16 Ochotona princeps brunnescens 1 #> 17 Ochotona princeps jewetti 1 #> 18 Ochotona princeps tutelata 1 #> 19 Ochotona princeps uinta 1 #> 20 Ochotona princeps ventorum 1
Spatial search service allows only to search on a point defined by latitude and longitude pair, with a radius (meters) from that point. All three parameters are required.
res <- spatialsearch(lat = 33.529, lon = -105.694, radius = 2000, limit = 10, messages = FALSE) res$data #> # A tibble: 10 × 62 #> month decimallongitude startdayofyear minimumelevationinmeters accessrights #> <chr> <chr> <chr> <chr> <chr> #> 1 07 -105.68633 193 2182.368 http://vertne… #> 2 07 -105.705479 196 2023.872 http://vertne… #> 3 07 -105.705479 196 2023.872 http://vertne… #> 4 07 -105.705479 196 2023.872 http://vertne… #> 5 07 -105.705479 196 2023.872 http://vertne… #> 6 07 -105.705479 196 2023.872 http://vertne… #> 7 07 -105.705479 196 2023.872 http://vertne… #> 8 07 -105.705479 196 2023.872 http://vertne… #> 9 07 -105.705479 196 2023.872 http://vertne… #> 10 07 -105.705479 196 2023.872 http://vertne… #> # ℹ 57 more variables: kingdom <chr>, day <chr>, #> # identificationverificationstatus <chr>, occurrenceid <chr>, #> # identificationqualifier <chr>, georeferenceddate <chr>, #> # verbatimeventdate <chr>, coordinateuncertaintyinmeters <chr>, #> # higherclassification <chr>, sex <chr>, year <chr>, specificepithet <chr>, #> # basisofrecord <chr>, geodeticdatum <chr>, occurrenceremarks <chr>, #> # highergeography <chr>, continent <chr>, scientificname <chr>, …
vertsearch()
provides a simple full text search against all fields. For more info see the docs. An example:
res <- vertsearch(taxon = "aves", state = "california", limit = 10) res$data #> # A tibble: 10 × 57 #> higherclassification stateprovince basisofrecord month decimallongitude #> <chr> <chr> <chr> <chr> <chr> #> 1 Animalia | Chordata | | … California PreservedSpe… 2 -121.7833 #> 2 Animalia | Chordata | | … California PreservedSpe… 6 -122.15 #> 3 Animalia | Chordata | | … California PreservedSpe… 5 -120.9014 #> 4 Animalia; Chordata; Aves;… South Caroli… PreservedSpe… 2 -79.86151 #> 5 Animalia; Chordata; Aves;… California PreservedSpe… 1 -121.93300 #> 6 Animalia; Chordata; Aves;… California PreservedSpe… 1 -121.93300 #> 7 Animalia; Chordata; Aves;… California PreservedSpe… 7 -121.85760 #> 8 Animalia; Chordata; Aves;… California PreservedSpe… 7 -121.85760 #> 9 Animalia; Chordata; Aves;… California PreservedSpe… 7 -121.85760 #> 10 Animalia; Chordata; Aves;… California PreservedSpe… 7 -121.85760 #> # ℹ 52 more variables: phylum <chr>, references <chr>, year <chr>, #> # startdayofyear <chr>, taxonrank <chr>, specificepithet <chr>, #> # bibliographiccitation <chr>, family <chr>, countrycode <chr>, #> # geodeticdatum <chr>, coordinateuncertaintyinmeters <chr>, #> # highergeography <chr>, continent <chr>, verbatimlocality <chr>, day <chr>, #> # kingdom <chr>, collectioncode <chr>, occurrencestatus <chr>, #> # coordinateprecision <chr>, institutioncode <chr>, scientificname <chr>, …
Limit the number of records returned (under 1000)
res <- vertsearch("(kansas state OR KSU)", limit = 200) res$data #> # A tibble: 200 × 78 #> individualcount georeferenceprotocol recordedby bibliographiccitation #> <chr> <chr> <chr> <chr> #> 1 8 GEOLocate (Rios & Bart, 201… H. W. Rob… Academy of Natural S… #> 2 11 GEOLocate (Rios & Bart, 201… H. W. Rob… Academy of Natural S… #> 3 3 GEOLocate (Rios & Bart, 201… H. W. Rob… Academy of Natural S… #> 4 <NA> <NA> <NA> California Academy o… #> 5 <NA> <NA> <NA> California Academy o… #> 6 <NA> <NA> <NA> California Academy o… #> 7 1 VertNet Georeferencing Guid… MCCOY, C … Carnegie Museum of N… #> 8 1 VertNet Georeferencing Guid… MCCOY, C … Carnegie Museum of N… #> 9 1 VertNet Georeferencing Guid… MCCOY, C … Carnegie Museum of N… #> 10 1 VertNet Georeferencing Guid… MCCOY, C … Carnegie Museum of N… #> # ℹ 190 more rows #> # ℹ 74 more variables: stateprovince <chr>, basisofrecord <chr>, month <chr>, #> # decimallongitude <chr>, phylum <chr>, references <chr>, #> # georeferencedby <chr>, year <chr>, taxonrank <chr>, specificepithet <chr>, #> # family <chr>, countrycode <chr>, locality <chr>, geodeticdatum <chr>, #> # coordinateuncertaintyinmeters <chr>, highergeography <chr>, #> # continent <chr>, day <chr>, kingdom <chr>, georeferenceddate <chr>, …
For searchbyterm()
, spatialsearch()
, and vertsearch()
, you can request more than 1000 records. VertNet limits each request to 1000 records, but internally in this package, if you request more than 1000 records, we'll continue to send requests to get all the records you want. See the VertNet docs for more information on this.
bigsearch()
specifies a termwise search (like searchbyterm()
), but requests that all available records be made available for download as a tab-delimited text file.
bigsearch(genus = "ochotona", rfile = "mydata", email = "you@gmail.com") #> Processing request... #> #> Download of records file 'mydata' requested for 'you@gmail.com' #> #> Query/URL: "http://api.vertnet-portal.appspot.com/api/download?q=%7B%22q%22:%22genus:ochotona%22,%22n%22:%22mydata%22,%22e%22:%22you@gmail.com%22%7D" #> #> Thank you! Download instructions will be sent by email.
In the previous examples, we've suppressed messages for more concise output, but you can set messages=TRUE
to get helpful messages - messages=TRUE
is also the default setting so if you don't specify that parameter messages will be printed to the console.
res <- searchbyterm(class = "Aves", state = "California", limit = 10, messages = TRUE)
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