3  Dowload data from figshare

According to https://info.figshare.com/:

Figshare’s industry leading repository infrastructure offers a single solution for storing and sharing data, papers, theses, media and much more

We are going to download the data from Ferrer-Paris (2018) directly from the figshare downloader link using functions from package jsonlite in R.

3.1 Local folder

First we will create a local folder to keep the data handy for analysis and then we will download the necessary data from different cloud storage services and repositories.

here::i_am("data-preparation/download-osf.qmd")

here() starts at /Users/z3529065/proyectos/Forests-Americas/RLE-example-dry-forest-guajira

target_dir <- "downloaded-data"
if (!file.exists(here::here(target_dir)))
  dir.create(here::here(target_dir))

3.2 Download from figshare

First we load the jsonlite library:

library(jsonlite)

We use the function read_json to parse the request for the article ID:

article_id <- '7488872'
response <- read_json(sprintf("https://api.figshare.com/v2/articles/%s", article_id))

The url we need is somewhere in the response:

str(response,1)

List of 48
 $ files              :List of 1
 $ authors            :List of 1
 $ custom_fields      : list()
 $ figshare_url       : chr "https://figshare.com/articles/dataset/IUCN_Red_List_of_Ecosystem_assessment_results_for_IVC_Forest_Macrogroups_"| __truncated__
 $ download_disabled  : logi FALSE
 $ description        : chr "Tables summarizing the results of the IUCN Red List of Ecosystems assessment of 136 tropical and temperate (exc"| __truncated__
 $ funding            : chr "Gordon and Betty Moore Foundation, Grant/Award Number: 3123"
 $ funding_list       :List of 2
 $ version            : int 1
 $ status             : chr "public"
 $ size               : int 83334
 $ created_date       : chr "2018-12-20T02:26:27Z"
 $ modified_date      : chr "2023-05-31T17:01:55Z"
 $ is_public          : logi TRUE
 $ is_confidential    : logi FALSE
 $ is_metadata_record : logi FALSE
 $ confidential_reason: chr "Publication scheduled for 2019-01-15"
 $ metadata_reason    : chr ""
 $ license            :List of 3
 $ tags               :List of 9
 $ categories         :List of 1
 $ references         :List of 1
 $ has_linked_file    : logi FALSE
 $ citation           : chr "Ferrer-Paris, José R. (2018). IUCN Red List of Ecosystem assessment results for IVC Forest Macrogroups in the A"| __truncated__
 $ related_materials  :List of 1
 $ is_embargoed       : logi FALSE
 $ embargo_date       : chr "2019-01-15"
 $ embargo_type       : NULL
 $ embargo_title      : chr ""
 $ embargo_reason     : chr "Publication scheduled for 2019-01-15"
 $ embargo_options    : list()
 $ id                 : int 7488872
 $ title              : chr "IUCN Red List of Ecosystem assessment results for IVC Forest Macrogroups in the Americas region"
 $ doi                : chr "10.6084/m9.figshare.7488872.v1"
 $ handle             : chr ""
 $ url                : chr "https://api.figshare.com/v2/articles/7488872"
 $ published_date     : chr "2018-12-20T02:26:27Z"
 $ thumb              : chr ""
 $ defined_type       : int 3
 $ defined_type_name  : chr "dataset"
 $ group_id           : NULL
 $ url_private_api    : chr "https://api.figshare.com/v2/account/articles/7488872"
 $ url_public_api     : chr "https://api.figshare.com/v2/articles/7488872"
 $ url_private_html   : chr "https://figshare.com/account/articles/7488872"
 $ url_public_html    : chr "https://figshare.com/articles/dataset/IUCN_Red_List_of_Ecosystem_assessment_results_for_IVC_Forest_Macrogroups_"| __truncated__
 $ timeline           :List of 2
 $ resource_title     : NULL
 $ resource_doi       : NULL

str(response$files[[1]],1)

List of 8
 $ id          : int 13874333
 $ name        : chr "20181123_MacrogroupsCountry.rda"
 $ size        : int 83334
 $ is_link_only: logi FALSE
 $ download_url: chr "https://ndownloader.figshare.com/files/13874333"
 $ supplied_md5: chr "4f6a59c01dfdab2541493ccfb28b9feb"
 $ computed_md5: chr "4f6a59c01dfdab2541493ccfb28b9feb"
 $ mimetype    : chr "application/gzip"

This is the info that we need:

url_source <- response$files[[1]]$download_url
dst_name <- response$files[[1]]$name

We use download.file to download from the source url to the destination path:

dst_path <- here::here(target_dir, dst_name)
if (!file.exists(dst_path))
    download.file(url_source, dst_path)

We can test the download with:

(load(dst_path))

[1] "Macrogroups.Global"         "Macrogroups.Country"       
[3] "SpatialCriteria.Global"     "SpatialCriteria.Country"   
[5] "FunctionalCriteria.Global"  "FunctionalCriteria.Country"

The R objects with a .Global suffix have the information for the global (i.e. ontinental) assessments, and the ones with .Country suffix have the information for the assessments within country boundaries.

Ferrer-Paris, José Rafael. 2018. “IUCN Red List of Ecosystem assessment results for IVC Forest Macrogroups in the Americas region.” figshare. https://doi.org/10.6084/m9.figshare.7488872.v1.