In AshwinAgrawal16/BiodiversityGSoC17: Integrating biodiversity data curation functionality.

Introduction

The Geospatial Quality API (GQ API) is a REST API created to provide access to a set of basic geospatial assessment functions over sets of primary biodiversity records. This package, rgeospatialquality, is built as a wrapper for the GQ API. It provides native access to the methods of the API and allows to use its functions from within an R environment. Below I will use the , rgeospatialquality,and ,rgbif, package to retrieve occurence data and send it the GQ API.

About Package

In this documentation there is a single function which retrieves GBIF occurrence data of all terrestrial mammals in Australia and then sends all of them to the Geospatial Quality API. The function code is below.

FUNCTION<-function(){
  if(requireNamespace("rgbif", quietly = TRUE)){
    library(rgbif)

    d1 <- occ_data(
      country = "AU",     # Country code for australia
      classKey= 359,      # Class code for mammalia
      from = 'gbif',
      limit=5000,
      minimal=FALSE,
      hasCoordinate = T

    )
  }

  if(requireNamespace("rgbif", quietly = TRUE)){
    d1 <- d1$data
  }


  ## Cleaning the data .
  library(tidyr)
  d1<-d1 %>% drop_na(decimalLatitude,decimalLongitude,countryCode,scientificName,name)

  d1$scientificName<-d1$name
  #Caveat: while the API accepts scientific names as specified in the DarwinCore Standard, currently some tools only work if the "Genus"+"Specific Epithet" binomial is provided in this field.
  #Thus, instead of "Puma concolor (Linnaeus, 1771)", we recommend using just "Puma concolor" in the 'scientificName' field.
  #To follow the abve code copying the name to scientificName column


  #Checking the values to conform to the DarwinCore Standard
  #decimalLatitude: Value for the Latitude in decimal degrees format (e.g. 42.332)
  #decimalLongitude: Value for the Longitude in decimal degrees format (e.g. -1.833)
  #countryCode: 2 character ISO code for the country
  #scientificName

  if(requireNamespace("rgbif", quietly = TRUE)){
    "decimalLatitude" %in% names(d1)
    "decimalLongitude" %in% names(d1)
    "countryCode" %in% names(d1)
    "scientificName" %in% names(d1)
  }

  #Pushing the data to Geospatial Quality API.
  #Hard limit of 1000 is set in the function add_flags.
  d5<-data.frame()
  library(rgeospatialquality)
  if(requireNamespace("rgbif")){
    i=0
    while(i<=4000)
    {
      if(i+1000>nrow(d1))
        dat<-subset(d1[(i+1):nrow(d1),])
      if(i+1000<=nrow(d1))
        dat<-subset(d1[(i+1):(i+1000),])

      i=i+1000

      ddd1 <- (add_flags(dat))
      ##Appending the data of flags in ome whole data frame
      d5<-rbind(d5,ddd1$flags)

    }
  }

  ##Appending the flagged data with original data.
  D<-cbind(d5,d1)

  #End
}

Plotting mammals occurence data in australia

Terrestrial mammals in Australia.

library(rgbif)
library(maptools)
d1 <- occ_data(
  country = "AU",     # Country code for australia
  classKey= 359,      # Class code for mammalia
  from = 'gbif',
  limit=500,
  minimal=FALSE
)

d1 <- d1$data
View(d1)
plot(d1[,4:3], cex=1.0, col='blue')
data(wrld_simpl)
plot(wrld_simpl, add=TRUE)

The above map is of australia with location of terrestrial mammals on it.

AshwinAgrawal16/BiodiversityGSoC17 documentation built on May 5, 2019, 8:12 a.m.