rvertnet v0.5.0

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Search 'Vertnet', a 'Database' of Vertebrate Specimen Records

Retrieve, map and summarize data from the 'VertNet.org' archives. Functions allow searching by many parameters, including 'taxonomic' names, places, and dates. In addition, there is an interface for conducting spatially delimited searches, and another for requesting large 'datasets' via email.

Readme

rvertnet

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rvertnet is a client for interacting with VertNet.org.

VertNet.org API docs: github.com/VertNet/webapp/wiki/The-API-search-function

Installation

Stable CRAN version

install.packages("rvertnet")

Or development version from GitHub

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

Search by term

Search for Aves in the state of California, limit to 10 records

res <- searchbyterm(class = "Aves", state = "California", lim = 10, verbose = FALSE)

Inspect metadata

res$meta
#> $request_date
#> [1] "2016-09-23T18:55:14.650960"
#> 
#> $response_records
#> [1] 10
#> 
#> $request_origin
#> [1] "45.523452,-122.676207"
#> 
#> $last_cursor
#> [1] "False:CqAFCuwCCr4C9wAAABn_____jIGJmo2LkZqL0o-QjYuek96WkZuah9LNz87L0s_N0s7Onv8AAP90baCgmYuMoKD_AAD_XZ6Pj5qRmJaRmv8AAP9zdG2WkZuah_8AAP9dm4ic_wAA_3N0bZuQnKCWm_8AAP9dnIqSidCdlo2b0oyPmpyWkpqRjNDKz8zPx_8AAP9zf5yKkonQnZaNm9KMj5qclpKakYzQys_Mz8f_AAD__wD-__6MgYmajYuRmovSj5CNi56T3paRm5qH0s3PzsvSz83Szs6e_wB0baCgmYuMoKD_AF2ej4-akZiWkZr_AHN0bZaRm5qH_wBdm4ic_wBzdG2bkJyglpv_AF2cipKJ0J2WjZvSjI-anJaSmpGM0MrPzM_H_wBzf5yKkonQnZaNm9KMj5qclpKakYzQys_Mz8f_AP_-EAohBN0EkB08Gxk5AAAAAOb___9IClAAWgsJaEr43cr5mgoQAmD9lv66BBINRG9jdW1lbnRJbmRleBr9AShBTkQgKElTICJjdXN0b21lcl9uYW1lIiAiYXBwZW5naW5lIikgKElTICJncm91cF9uYW1lIiAic352ZXJ0bmV0LXBvcnRhbCIpIChJUyAibmFtZXNwYWNlIiAiaW5kZXgtMjAxNC0wMi0xMWEiKSAoSVMgImluZGV4X25hbWUiICJkd2MiKSAoQU5EIChRVCAiQXZlcyIgInJ0ZXh0X2NsYXNzIikgKE9SIChJUyAicmF0b21fc3RhdGVwcm92aW5jZSIgImNhbGlmb3JuaWEiKSAoUVQgIkNhbGlmb3JuaWEiICJydGV4dF9zdGF0ZXByb3ZpbmNlIikpKSk6GQoMKE4gb3JkZXJfaWQpEAEZAAAAAAAA8P9KBQgAQOgH"
#> 
#> $limit
#> [1] 10
#> 
#> $query_version
#> [1] "search.py 2015-08-29T21:04:44+02:00"
#> 
#> $matching_records
#> [1] ">10000"
#> 
#> $api_version
#> [1] "api.py 2015-09-02T11:09:38+02:00"

Inspect data. A dplyr data.frame is given back, so you get a nice brief data summary:

res$data[,1:5]
#> # A tibble: 10 × 5
#>                 modified language                            accessrights
#>                    <chr>    <chr>                                   <chr>
#> 1             2015-01-06       en                                    <NA>
#> 2             2015-01-06       en                                    <NA>
#> 3  2015-05-11 07:55:08.0       en http://vertnet.org/resources/norms.html
#> 4  2015-05-11 07:55:08.0       en http://vertnet.org/resources/norms.html
#> 5  2015-08-26 13:10:07.0       en http://vertnet.org/resources/norms.html
#> 6  2015-08-26 13:10:07.0       en http://vertnet.org/resources/norms.html
#> 7  2015-08-26 13:10:07.0       en http://vertnet.org/resources/norms.html
#> 8  2015-08-26 13:10:07.0       en http://vertnet.org/resources/norms.html
#> 9  2015-08-26 13:10:07.0       en http://vertnet.org/resources/norms.html
#> 10 2015-08-26 13:10:07.0       en http://vertnet.org/resources/norms.html
#> # ... with 2 more variables: references <chr>, institutionid <chr>

Search for Mustela nigripes in the states of Wyoming or South Dakota, limit to 20 records

res <- searchbyterm(specificepithet = "nigripes", state = "(wyoming OR south dakota)", limit = 20, verbose = FALSE)
res$data[,1:5]
#> # A tibble: 19 × 5
#>                 modified language
#>                    <chr>    <chr>
#> 1  2010-01-14 13:06:23.0       en
#> 2  2011-11-17 12:02:57.0       en
#> 3             2013-08-07       en
#> 4  2015-04-14 15:45:27.0       en
#> 5  2015-04-17 17:39:57.0       en
#> 6  2015-08-18 10:24:17.0       en
#> 7             2016-06-02       en
#> 8                   <NA>     <NA>
#> 9                   <NA>     <NA>
#> 10                  <NA>     <NA>
#> 11                  <NA>     <NA>
#> 12                  <NA>     <NA>
#> 13                  <NA>     <NA>
#> 14                  <NA>     <NA>
#> 15                  <NA>     <NA>
#> 16                  <NA>     <NA>
#> 17                  <NA>     <NA>
#> 18                  <NA>     <NA>
#> 19                  <NA>     <NA>
#> # ... with 3 more variables: accessrights <chr>, references <chr>,
#> #   institutionid <chr>

dplyr downstream

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: 25 × 2
#>                   scientificname count
#>                            <chr> <int>
#> 1              Ochotona princeps   287
#> 2    Ochotona princeps saxatilis   169
#> 3               Ochotona pallasi   114
#> 4        Ochotona princeps muiri   107
#> 5            Ochotona hyperborea    30
#> 6     Ochotona princeps figginsi    18
#> 7              Ochotona dauurica    14
#> 8     Ochotona princeps princeps     9
#> 9  Ochotona princeps brunnescens     8
#> 10      Ochotona princeps cuppes     8
#> # ... with 15 more rows

Big data

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", rf = "pikaRecords", email = "big@@search.luv")
#> 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.
res <- spatialsearch(lat = 33.529, lon = -105.694, radius = 2000, limit = 10, verbose = FALSE)
res$data[,1:5]
#> # A tibble: 10 × 5
#>                 modified language
#>                    <chr>    <chr>
#> 1  2013-09-10 12:55:00.0       en
#> 2  2013-09-10 12:55:00.0       en
#> 3  2013-09-10 12:55:00.0       en
#> 4  2014-01-14 16:04:11.0       en
#> 5  2014-06-03 17:37:34.0       en
#> 6  2014-09-09 14:04:14.0       en
#> 7  2014-09-09 14:04:14.0       en
#> 8  2015-08-03 19:48:08.0       en
#> 9  2015-09-08 00:33:35.0       en
#> 10                  <NA>       en
#> # ... with 3 more variables: accessrights <chr>, references <chr>,
#> #   institutionid <chr>

Contributors

Meta

  • Please report any issues or bugs.
  • License: MIT
  • Get citation information for rvertnet in R doing citation(package = 'rvertnet')

ropensci_footer

Functions in rvertnet

Name Description
spatialsearch Find records within some distance of a point given latitude and longitude.
vertmap Make a simple map to visualize VertNet data.
rvertnet-defunct Defunct functions in rvertnet
vertavailablemaps This function is defunct.
vert_id Search by Vertnet occurrence ID
searchbyterm Search for records using keywords/terms to control how your query is interpreted
bigsearch Request to download a large number of VertNet records.
rvertnet-package Search VertNet archives using R
dump Use Vertnet taxon specific dump from KNB
vertlocations This function is defunct.
vertoccurrence This function is defunct.
vertoccurrencecount This function is defunct.
vertsummary Summarize a set of records downloaded from VertNet.
verttaxa This function is defunct.
vertsearch Find records using a global full-text search of VertNet archives.
vertproviders This function is defunct.
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Details

License MIT + file LICENSE
LazyData true
URL https://github.com/ropensci/rvertnet
BugReports https://github.com/ropensci/rvertnet/issues
VignetteBuilder knitr
RoxygenNote 5.0.1
NeedsCompilation no
Packaged 2016-09-23 19:11:02 UTC; sacmac
Repository CRAN
Date/Publication 2016-09-23 22:40:00

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