The purpose of this package is to connect R environment to
speciesLink, a collaborative network that includes the participation
of hundreds of biological collections in Brazil and abroad, whose main
objective is to give access to anyone interested in the data about the
records held by collections, and observation data
(cria.org.br).
This package uses CRIA speciesLink API v.0.1 beta (CRIA) as source of the data and the Exsiccatae service (INCT-HVFF) as images source.
You can install the released version of splinkr from
GitHub with:
if (!require(devtools)) install.packages("devtools")
devtools::install_github("cadubio/splinkr")
There are tree functions in package: splinkr_datasets,
splinkr_records and splinkr_images.
# load package
library(splinkr)
The function splinkr_datasets() with no arguments returns a tibble
with all datasets of biological collections included in speciesLink
network.
splinkr_datasets()
#> # A tibble: 529 x 9
#> collectionCode collectionName institutionCode institutionName scope
#> <chr> <chr> <chr> <chr> <chr>
#> 1 AcariESALQ Coleção de Ác… USP Universidade d… anim…
#> 2 ALCB Herbário Alex… UFBA Universidade F… plan…
#> 3 AMNH-Bee Collaborative… AMNH American Museu… anim…
#> 4 ANSP-Ichthyol… The Academy o… ANSP The Academy of… anim…
#> 5 Aranhas-Solob… Coleção de Ar… UFPR Universidade F… anim…
#> 6 ARAR Coleção Aracn… UPF Universidade d… anim…
#> 7 ASE Herbário da U… UFS Universidade F… plan…
#> 8 ASU-Lichen Arizona State… ASU Arizona State … plan…
#> 9 ASU-Plants Arizona State… ASU Arizona State … plan…
#> 10 B Herbarium Ber… FU-Berlin Freie Universi… plan…
#> # … with 519 more rows, and 4 more variables: numberOfRecords <chr>,
#> # location <chr>, keywords_pt <chr>, keywords_en <chr>
Pass one term to filter argument filtering all variables (columns) of
datasets.
splinkr_datasets(filter = "universidade")
#> # A tibble: 326 x 9
#> collectionCode collectionName institutionCode institutionName scope
#> <chr> <chr> <chr> <chr> <chr>
#> 1 AcariESALQ Coleção de Ác… USP Universidade d… anim…
#> 2 ALCB Herbário Alex… UFBA Universidade F… plan…
#> 3 Aranhas-Solob… Coleção de Ar… UFPR Universidade F… anim…
#> 4 ARAR Coleção Aracn… UPF Universidade d… anim…
#> 5 ASE Herbário da U… UFS Universidade F… plan…
#> 6 BHCB Herbário da U… UFMG Universidade F… plan…
#> 7 BHCB-Bryophyta Herbário da U… UFMG Universidade F… plan…
#> 8 BHCB-SL Herbário da U… UFMG Universidade F… plan…
#> 9 BMA Herbário Mara… UFMA Universidade F… plan…
#> 10 BOTU Herbário Irin… UNESP Universidade E… plan…
#> # … with 316 more rows, and 4 more variables: numberOfRecords <chr>,
#> # location <chr>, keywords_pt <chr>, keywords_en <chr>
If more than one term is passed to filter, intersection filtering is
performed, that is, the search with second term is only performed on
subset obtained from filtering with first term. The search with third
term is only done in subset of second term and so on…
splinkr_datasets(filter = c("universidade", "herbário", "brasil"))
#> # A tibble: 135 x 9
#> collectionCode collectionName institutionCode institutionName scope
#> <chr> <chr> <chr> <chr> <chr>
#> 1 ALCB Herbário Alex… UFBA Universidade F… plan…
#> 2 ASE Herbário da U… UFS Universidade F… plan…
#> 3 BHCB Herbário da U… UFMG Universidade F… plan…
#> 4 BHCB-Bryophyta Herbário da U… UFMG Universidade F… plan…
#> 5 BHCB-SL Herbário da U… UFMG Universidade F… plan…
#> 6 BMA Herbário Mara… UFMA Universidade F… plan…
#> 7 BOTU Herbário Irin… UNESP Universidade E… plan…
#> 8 BOTU-Fungi Herbário Irin… UNESP Universidade E… plan…
#> 9 CESJ Herbário Leop… UFJF Universidade F… plan…
#> 10 CGMS Herbário da F… UFMS Universidade F… plan…
#> # … with 125 more rows, and 4 more variables: numberOfRecords <chr>,
#> # location <chr>, keywords_pt <chr>, keywords_en <chr>
Note that filtering do not matches case, but matches with portuguese diacritical signs.
splinkr_datasets(filter = c("Herbario"))
#> # A tibble: 3 x 9
#> collectionCode collectionName institutionCode institutionName scope
#> <chr> <chr> <chr> <chr> <chr>
#> 1 HJ Herbario Jata… UFJ Universidade F… plan…
#> 2 HUEFS Herbario da U… UEFS Universidade E… plan…
#> 3 MBML-Herbario Herbário Mell… INMA Instituto Naci… plan…
#> # … with 4 more variables: numberOfRecords <chr>, location <chr>,
#> # keywords_pt <chr>, keywords_en <chr>
splinkr_datasets(filter = c("herbário"))
#> # A tibble: 203 x 9
#> collectionCode collectionName institutionCode institutionName scope
#> <chr> <chr> <chr> <chr> <chr>
#> 1 ALCB Herbário Alex… UFBA Universidade F… plan…
#> 2 ASE Herbário da U… UFS Universidade F… plan…
#> 3 ASU-Plants Arizona State… ASU Arizona State … plan…
#> 4 B Herbarium Ber… FU-Berlin Freie Universi… plan…
#> 5 BAH Herbário Antô… EBDA Empresa Baiana… plan…
#> 6 BHCB Herbário da U… UFMG Universidade F… plan…
#> 7 BHCB-Bryophyta Herbário da U… UFMG Universidade F… plan…
#> 8 BHCB-SL Herbário da U… UFMG Universidade F… plan…
#> 9 BHZB Herbário do J… FZB-BH Fundação Zoo-B… plan…
#> 10 BLA Brazilian Lab… FEPAGRO Fundação Estad… plan…
#> # … with 193 more rows, and 4 more variables: numberOfRecords <chr>,
#> # location <chr>, keywords_pt <chr>, keywords_en <chr>
This is the main function of the package. It provides a search engine
for the more than 14 million speciesLink records. All arguments are
NULL by default. Arguments scientificName, barcode and
catalogNumber are mutualy excludent, on the other hand, one of the
them can mixed with all other arguments. See list of arguments below.
| Argument | Options | Example |
|---|---|---|
| barcode | character vector | c("NY00000001", "FPS00257", "FCM00096") |
| basisOfRecord | PreservedSpecimen, LivingSpecimen, FossilSpecimen, HumanObservation, MachineObservation, MaterialSample | c(“PreservedSpecimen”) |
| collectionCode | character vector | c("FIOCRUZ-CEIOC", "UEC", "HUEFS") |
| catalogNumber | character vector, embranco, nãobranco | c("435643", "P234576", "embranco) |
| collector | collector name | c("Siqueira", "Almeida F") |
| collectorNumber | character vector | c("125", "1897A") |
| yearCollected | four-digits year | c(1887, 1897, 2000) |
| identifiedBy | character vector | c("Siqueira CE") |
| yearIdentified | four-digits year | c(1997, 2015) |
| kingdom | character vector | c("Plantae", "Animalia", "Fungi") |
| phylum | character vector | c("Arthropoda", "Nematoda") |
| class | character vector | c("Reptilia", "Amphibia") |
| order | character vector | c("Crocodilia", "Anura") |
| family | character vector | c("Bromeliaceae", "Apidae") |
| genus | character vector | c("Tabebuia", "Bacillus", "Hoplias") |
| scientificName | character vector | c("Bothrops neuwiedii matogrossensis", "Leishmania braziliensis") |
| typus | NULL, yes | “yes” |
| country | character vector | c("Brasil", "Argentina") |
| stateProvince | character vector | c("SP", "Santa Catarina", "MT") |
| county | character vector | c("São José", "Anitápolis", "Rio Branco") |
| locality | character vector | c("pedra branca", "fazendinha") |
| maxRecords | character vector | “5” |
| redlist | NULL, yes | “yes” |
Code examples
# scientific name query
splinkr_records(scientificName = "Dyckia encholirioides var. rubra")
#> Warning in names(x) == varNames: comprimento do objeto maior não é múltiplo do
#> comprimento do objeto menor
#> # A tibble: 2 x 25
#> modified institutionCode collectionCode catalogNumber basisOfRecord kingdom
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 2016-02… BGBM B B 10 0248907 S Plantae
#> 2 2018-06… MO MOBOT 2452813 PreservedSpe… Plantae
#> # … with 19 more variables: family <chr>, genus <chr>, specificEpithet <chr>,
#> # infraspecificEpithet <chr>, scientificName <chr>,
#> # scientificNameAuthorship <chr>, typeStatus <chr>, recordedBy <chr>,
#> # recordNumber <chr>, continentOcean <chr>, country <chr>, locality <chr>,
#> # occurrenceRemarks <chr>, barcode <chr>, imagecode <chr>, year <chr>,
#> # month <chr>, day <chr>, stateProvince <chr>
splinkr_records(scientificName = c("Acianthera saundersiana", "Anathallis microphyta"),
collector = "Siqueira")
#> # A tibble: 12 x 36
#> modified institutionCode collectionCode catalogNumber basisOfRecord kingdom
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 2020-08… UFSC FLOR 37752 PreservedSpe… Plantae
#> 2 2020-08… UFSC FLOR 37751 PreservedSpe… Plantae
#> 3 2020-08… UFSC FLOR 50339 PreservedSpe… Plantae
#> 4 2020-08… UFSC FLOR 37753 PreservedSpe… Plantae
#> 5 2020-08… UFSC FLOR 37802 PreservedSpe… Plantae
#> 6 2020-08… UFSC FLOR 37804 PreservedSpe… Plantae
#> 7 2020-08… UFSC FLOR 37759 PreservedSpe… Plantae
#> 8 2020-08… UFSC FLOR 37758 PreservedSpe… Plantae
#> 9 2020-08… UFSC FLOR 50341 PreservedSpe… Plantae
#> 10 2020-08… UFSC FLOR 50761 PreservedSpe… Plantae
#> 11 2020-08… UFSC FLOR 51722 PreservedSpe… Plantae
#> 12 2020-08… UFSC FLOR 59299 PreservedSpe… Plantae
#> # … with 30 more variables: order <chr>, family <chr>, genus <chr>,
#> # specificEpithet <chr>, scientificName <chr>,
#> # scientificNameAuthorship <chr>, identifiedBy <chr>, recordedBy <chr>,
#> # recordNumber <chr>, year <chr>, month <chr>, day <chr>, country <chr>,
#> # stateProvince <chr>, county <chr>, locality <chr>, decimalLongitude <chr>,
#> # decimalLatitude <chr>, verbatimLongitude <chr>, verbatimLatitude <chr>,
#> # minimumElevationInMeters <chr>, maximumElevationInMeters <chr>,
#> # occurrenceRemarks <chr>, barcode <chr>, yearIdentified <chr>,
#> # monthIdentified <chr>, dayIdentified <chr>, coordinatePrecision <chr>,
#> # geoFlag <chr>, imagecode <chr>
# Returns only type species
splinkr_records(scientificName = c("Campylocentrum insulare", "Acianthera saundersiana"), collectionCode = "FLOR", typus = "yes")
#> # A tibble: 1 x 31
#> modified institutionCode collectionCode catalogNumber basisOfRecord kingdom
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 2020-08… UFSC FLOR 40000 PreservedSpe… Plantae
#> # … with 25 more variables: order <chr>, family <chr>, genus <chr>,
#> # specificEpithet <chr>, scientificName <chr>,
#> # scientificNameAuthorship <chr>, identifiedBy <chr>, yearIdentified <chr>,
#> # typeStatus <chr>, recordedBy <chr>, recordNumber <chr>, year <chr>,
#> # month <chr>, country <chr>, stateProvince <chr>, county <chr>,
#> # locality <chr>, decimalLongitude <chr>, decimalLatitude <chr>,
#> # verbatimLongitude <chr>, verbatimLatitude <chr>,
#> # minimumElevationInMeters <chr>, maximumElevationInMeters <chr>,
#> # occurrenceRemarks <chr>, barcode <chr>
A large number of scientific names may be passed but the return may take
a while, so it possible limit the number of records to return with
maxrecords argument
# Vector names
nomes <- c("Abarema turbinata", "Comolia villosa", "Stylosanthes campestris",
"Vochysia floribunda", "Eugenia platyphylla", "Chaetocalyx acutifolia",
"Actinocephalus ochrocephalus", "Cicuta douglasii", "Annona senegalensis",
"Hexasepalum radula", "Trichosalpinx dura", "Allophylus sericeus",
"Microlicia juniperina", "Campomanesia pubescens", "Luxemburgia ciliosa",
"Dalechampia humilis", "Croton heliotropiifolius", "Senna alata",
"Ipomoea dichotoma", "Arundo donax")
# Note that maxrecords must be passed as a character (quoted number)
splinkr_records(scientificName = nomes, maxrecords = "20")
The goal of this function is to provide a relatively quick way to view images of collections. According (cria.org.br) there are more than three million records with images. Package imager is used to display this images.
In the future an integration with imageJ may be provided to download and examine images from specimen records.
# Display image by `imagecode`
splinkr_images(imagecode = c("FLOR0037759", "UEC190851", "FURB53840"))
# Display image by `scientificName`
splinkr_images(scientificName = c("Spigelia insignis", "Anathallis kleinii"))
Example of display function from package imager
Example display function from package imager
The results of splinkr_records can be passed via %>% (pipe) to
splinkr_images to display images.
# View images of genus 'Campylocentrum' from UPCB herbarium
splinkr_records(scientificName = "Campylocentrum", collectionCode = "UPCB") %>%
splinkr_images(imagecode = .)
CRIA, Centro de Referência em Informação Ambiental. speciesLink API v.0.1 beta. (api.splink.org.br), accessed 5.10.2020.
INCT-HVFF, Herbário Virtual da Flora e dos Fungos. (reflora-cdc.cria.org.br/inct/exsiccatae), accessed 5.10.2020.
Duncan Temple Lang (2020). XML: Tools for Parsing and Generating XML Within R and S-Plus. R package version 3.99-0.5. (CRAN)
Hadley Wickham, Romain François, Lionel Henry and Kirill Müller (2020).
dplyr: A Grammar of Data Manipulation. R package version 1.0.2.
(CRAN)
Hadley Wickham, Jim Hester and Jeroen Ooms (2020). xml2: Parse XML. R
package version 1.3.2. (CRAN)
Kirill Müller and Hadley Wickham (2020). tibble: Simple Data Frames. R
package version 3.0.3.
(CRAN)
Lionel Henry and Hadley Wickham (2020). purrr: Functional Programming
Tools. R package version 0.3.4.
(CRAN)
Simon Barthelme (2020). imager: Image Processing Library Based on
‘CImg’. R package version 0.42.3.
(CRAN)
Stefan Milton Bache and Hadley Wickham (2014). magrittr: A
Forward-Pipe Operator for R. R package version 1.5.
(CRAN)
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