rcrossref.R

# these are code chunks from the rcrossref walkthrough
# binder link: https://mybinder.org/v2/gh/ciakovx/ciakovx.github.io/master?filepath=rcrossref.ipynb


library(knitr)
library(tidyverse)
library(janitor)
library(png)
library(rcrossref)
library(roadoi)
library(listviewer)
library(usethis)


# Setting up rcrossref ----------------------------------------------------

# add your email address to rcrossref API calls
usethis::edit_r_environ()
# type in the following, using your own email address, save, then go to
# Session > Restart R
# crossref_email=name@example.com



# Getting journal details -------------------------------------------------

# assign the PLoS ISSN
plosone_issn <- '1932-6203'

# get information about the journal
plosone_details <- rcrossref::cr_journals(issn = plosone_issn, works = FALSE)
str(plosone_details)


# rerun the call, getting information about the journal and pluck the data
plosone_details <- rcrossref::cr_journals(issn = plosone_issn, works = FALSE) %>%
  purrr::pluck("data")

# View the data frame
View(plosone_details)


#display information about the data frame
str(plosone_details)


# dimensions: 1 row, 53 columns
dim(plosone_details)


# number of rows
nrow(plosone_details)



# number of columns
ncol(plosone_details)



# column names
names(plosone_details)



# print the publisher variable
plosone_details$publisher



# print the total number of DOIs
plosone_details$total_dois



# is funder data current on deposits?
plosone_details$deposits_funders_current



# Getting journal publications by issn ------------------------------------

# get metadata on articles by setting works = TRUE
plosone_publications <- cr_journals(issn = plosone_issn, works = TRUE, limit = 25) %>%
  pluck("data")



# print dimensions of this data frame
dim(plosone_publications)



# print column names
names(plosone_publications)



# print select columns from the data frame
plosone_publications %>%
  dplyr::select(title, doi, volume, issue, page, issued, url, publisher, reference.count, type, issn)



# Getting multiple publications by issn -----------------------------------

# assign the JAMA and JAH ISSNs
jama_issn <- '1538-3598'
jah_issn <- '0021-8723'

# get the last 10 publications on deposit from each journal. For multiple ISSNs, use c() to combine them
jah_jama_publications <- rcrossref::cr_journals(issn = c(jama_issn, jah_issn), works = T, limit = 10) %>%
  purrr::pluck("data")



# print column names
names(jah_jama_publications)



# print data frame with select columns
jah_jama_publications %>%
  dplyr::select(title, doi, volume, issue, page, issued, url, publisher, reference.count, type, issn)



# Filter to select some parameters ----------------------------------------

# assign the JLSC ISSN
jlsc_issn <- "2162-3309"

# get articles published since January 1, 2019
jlsc_publications_2019 <- rcrossref::cr_journals(issn = jlsc_issn, works = T, 
                                                 filter = c(from_pub_date='2019-01-01')) %>%
  purrr::pluck("data")

# print the dataframe with select column
jlsc_publications_2019 %>%
  dplyr::select(title, doi, volume, issue, issued, url, publisher, reference.count, type, issn)



# Filtering by funder -----------------------------------------------------

# assign the PLoS ONE ISSN and the NIH Funder DOI
plosone_issn <- '1932-6203'
nih_funder_doi <- '10.13039/100000002'

# get articles published in PLoS since 3/1 funded by NIH
plosone_publications_nih <- rcrossref::cr_journals(issn = plosone_issn, works = T, limit = 25,
                                                   filter = c(award.funder = nih_funder_doi,
                                                              from_pub_date = '2020-03-01')) %>%
  purrr::pluck("data")



# print the dataframe, first unnesting the funder column
plosone_publications_nih %>%
    tidyr::unnest(funder)



# filtering by license ----------------------------------------------------

# assign the PLoS ONE ISSN and get journal details by setting works = FALSE
plosone_issn <- '1932-6203'
plosone_details <- rcrossref::cr_journals(issn = plosone_issn, works = FALSE) %>%
  purrr::pluck("data")



# is article licensing data on file current?
plosone_details$deposits_licenses_current



# get last 25 articles on file where has_license is TRUE
plosone_license <- rcrossref::cr_journals(issn = plosone_issn, works = T, limit = 25, filter = c(`has_license` = TRUE)) %>% 
  pluck("data")



# print the data with select columns
plosone_license %>%
  dplyr::select(title, doi, volume, issue, page, issued, url, publisher, reference.count, type, issn, license)



# print the data frame with license unnested. The .drop argument will drop all other list columns.
plosone_license %>%
  tidyr::unnest(license, .drop = TRUE)



# Filtering rows and selecting columns with dplyr -------------------------

# assign the JLSC ISSN and get all publications after January 1, 2019
jlsc_issn <- "2162-3309"
jlsc_publications_2019 <- rcrossref::cr_journals(issn = jlsc_issn, works = T, limit = 25,
                                                 filter = c(from_pub_date='2019-01-01')) %>%
  purrr::pluck("data")

# print the data frame with select columns
jlsc_publications_2019 %>%
  dplyr::select(title, doi, volume, issue, issued, url, publisher, reference.count, type, issn)



# use filter from dplyr to get only volume 8, issue 1
jlsc_8_1 <- jlsc_publications_2019 %>%
  dplyr::filter(volume == "8",
         issue == "1") 

# print the data frame with select columns
jlsc_8_1 %>%
  dplyr::select(title, doi, volume, issue, issued, url, publisher, reference.count, type, issn)



jah_jama_publications$issn[1]



# filter to get "The Five Laws of OER" article by DOI
jlsc_article <- jlsc_publications_2019 %>%
  dplyr::filter(doi == "10.7710/2162-3309.2299") 

# print data frame with select columns
jlsc_article %>%
  dplyr::select(title, doi, volume, issue, issued, url, publisher, reference.count, type, issn)



# use str_detect to search the title column for articles that include the term OER
jlsc_article <- jlsc_publications_2019 %>%
  dplyr::filter(stringr::str_detect(title, "OER"))

# print the data frame with select column
jlsc_article %>%
  dplyr::select(title, doi, volume, issue, issued, url, publisher, reference.count, type, issn)


# Field query by title ----------------------------------------------------

# assign JLSC ISSN and query the bibliographic field for terms mentioning open access. 
jlsc_issn <- "2162-3309"
jlsc_publications_oa <- rcrossref::cr_journals(issn = jlsc_issn, works = T, limit = 25,
                                            flq = c(`query.bibliographic` = 'open access')) %>%
  purrr::pluck("data")

# print the data frame with select columns
jlsc_publications_oa %>%
  dplyr::select(title, doi, volume, issue, issued, issn, author)



# Use the query.author field query to find JLSC articles with author name Salo
jlsc_publications_auth <- rcrossref::cr_journals(issn = jlsc_issn, works = T, limit = 25,
                                            flq = c(`query.author` = 'salo')) %>%
  purrr::pluck("data")

# print the data frame with select columns
jlsc_publications_auth %>%
  dplyr::select(title, doi, volume, issue, issued, url, publisher, reference.count, type, issn)



# Viewing the JSON file ---------------------------------------------------

# assign the PLOS ISSN and get the last 25 articles on deposit
plosone_issn <- '1932-6203'
plosone_publications <- cr_journals(issn = plosone_issn, works = TRUE, limit = 5) %>%
  pluck("data")

listviewer::jsonedit(plosone_publications, mode = "view")



# Using cr_works to get data on articles ----------------------------------

# Get metadata for a single article by DOI
jlsc_ku_oa <- cr_works(dois = '10.7710/2162-3309.1252') %>%
  purrr::pluck("data")

# print the data frame with select columns
jlsc_ku_oa %>%
  dplyr::select(title, doi, volume, issue, page, issued, url, publisher, reference.count, type, issn)



# Use c() to create a vector of DOIs
my_dois <- c("10.2139/ssrn.2697412", 
                        "10.1016/j.joi.2016.08.002", 
                        "10.1371/journal.pone.0020961", 
                        "10.3389/fpsyg.2018.01487", 
                        "10.1038/d41586-018-00104-7", 
                        "10.12688/f1000research.8460.2", 
                        "10.7551/mitpress/9286.001.0001")

# pass the my_dois vector to cr_works()
my_dois_works <- rcrossref::cr_works(dois = my_dois) %>%
  pluck("data")

# print the data frame with select columns
my_dois_works %>%
  dplyr::select(title, doi, volume, issue, page, issued, url, publisher, reference.count, type, issn)



# Unnesting list columns --------------------------------------------------

# query to get data on a specific PLOS article
plos_article <- cr_works(dois = '10.1371/journal.pone.0228782') %>%
  purrr::pluck("data")

# print the type of each column (e.g. character, numeric, logical, list)
purrr::map_chr(plos_article, typeof)



# unnest author column
plos_article %>%
    tidyr::unnest(author, .drop = TRUE)


# Getting more than 1000 results with cursor ------------------------------

philo_issn <- '2053-9223'
philo_details <- rcrossref::cr_journals(philo_issn, works = FALSE) %>%
  pluck("data")
philo_details$total_dois


## philo_articles <- rcrossref::cr_journals(philo_issn, works = TRUE, cursor = "*", cursor_max = 8534) %>%
##   pluck("data")



# specifying field queries to cr_works ------------------------------------

# do a general query for the term open access and a field query to return results where the author name includes Suber
suber_oa <- cr_works(query = 'open+access', flq = c(`query.author` = 'suber')) %>%
  pluck("data")

# print the data frame with select columns
suber_oa %>%
  dplyr::select(title, doi, volume, issue, page, issued, url, publisher, reference.count, type, issn)



# use filter() from dplyr to filter that result to include only books
suber_oa_books <- suber_oa %>%
  filter(type == "book")

# print the data frame with select columns
suber_oa_books %>%
  dplyr::select(title, doi, volume, issue, page, issued, url, publisher, reference.count, type, issn)



# run a different cr_works() query with author set to Suber and his book's ISBN passed to query.bibliographic
suber_isbn <- cr_works(flq = c(`query.author` = 'suber',
                           `query.bibliographic` = '9780262301732')) %>%
  pluck("data")

# print the data frame with select columns
suber_isbn %>%
  dplyr::select(title, doi, issued, url, publisher, type, author)



# Getting formatted references in a text file -----------------------------

# Use c() to create a vector of DOIs
my_dois <- c("10.2139/ssrn.2697412", 
                        "10.1016/j.joi.2016.08.002", 
                        "10.1371/journal.pone.0020961", 
                        "10.3389/fpsyg.2018.01487", 
                        "10.1038/d41586-018-00104-7", 
                        "10.12688/f1000research.8460.2", 
                        "10.7551/mitpress/9286.001.0001")

# Use cr_cn to get back citations formatted in Chicago for those DOIs
my_citations <- rcrossref::cr_cn(my_dois,
                                 format = "text",
                                 style = "chicago-note-bibliography") %>% 
  purrr::map_chr(., purrr::pluck, 1)

# print the formatted citations
my_citations

# write the formatted citations to a text file
## writeLines(my_citations, "my_citations_text.txt")



# look at the first 15 styles Crossref offers
rcrossref::get_styles()[1:15]



# Getting formatted references in a bibtex or RIS file --------------------

## # Use cr_cn() to get BibTeX files for my DOIs
## my_citations_bibtex <- rcrossref::cr_cn(my_dois, format = "bibtex") %>%
##   purrr::map_chr(., purrr::pluck, 1)


## # write to bibtex file
## writeLines(my_citations_bibtex, "my_citations_bibtex.bib")



# getting works from a typed citation in a word doc or text file ----------

# read in a CSV file of citations
my_references <- read.csv("DIRECTORY YOUR DATA IS SAVED/references.txt", stringsAsFactors = FALSE)

# print the file
my_references



# loop through the references column, using cr_works() to look the item up and return the top 5 hits
my_references_works_list <- purrr::map(
  my_references$reference,
  function(x) {
    print(x)
    my_works <- rcrossref::cr_works(query = x, limit = 5) %>%
      purrr::pluck("data")
  })



# for each reference looked up, get back the first result
my_references_works_df <- my_references_works_list %>%
  purrr::map_dfr(., function(x) {
    x[1, ]
  })

# print the data frame with select columns
my_references_works_df %>%
  dplyr::select(title, doi, volume, issue, page, issued, url, publisher, reference.count, type, issn)



# print the title column
my_references_works_df$title


my_references_works_list %>%
  purrr::pluck(5, "title")


my_references_works_df <- my_references_works_df %>%
  dplyr::slice(-5)


suber <- my_references_works_list %>%
  purrr::pluck(7)
suber


suber_correct <- suber %>%
  dplyr::filter(isbn == "9780262301732")
my_references_works_df <- my_references_works_df %>%
  dplyr::slice(-6) %>%
  bind_rows(suber_correct)


## my_filepath <- "C:/EXAMPLE/crossref/data"


## jah_jama_publications_auth <- jah_jama_publications %>%
##   dplyr::filter(!purrr::map_lgl(author, is.null)) %>%
##   tidyr::unnest(author, .drop = TRUE) %>%
##   dplyr::bind_rows(jah_jama_publications %>%
##                      dplyr::filter(map_lgl(author, is.null)) %>%
##                      dplyr::select(-author, -link))
## readr::write_csv(jah_jama_publications_auth, file.path(my_filepath, "jah_jama_publications_auth.csv"))


## jah_jama_publications_short <- jah_jama_publications %>%
##   dplyr::select_if(purrr::negate(is.list))
## readr::write_csv(jah_jama_publications_author, file.path(my_filepath, "jah_jama_publications_short.csv"))


## jah_jama_publications_mutated <- jah_jama_publications %>%
##   dplyr::mutate(author = as.character(author)) %>%
##   dplyr::mutate(link = as.character(link))
## readr::write_csv(jah_jama_publications_mutated, file.path(my_filepath, "jah_jama_publications_mutated.csv"))


# using roadoi to check for open access -----------------------------------


# load the roadoi package
library(roadoi)



# Use c() to create a vector of DOIs
my_dois <- c("10.2139/ssrn.2697412", 
                        "10.1016/j.joi.2016.08.002", 
                        "10.1371/journal.pone.0020961", 
                        "10.3389/fpsyg.2018.01487", 
                        "10.1038/d41586-018-00104-7", 
                        "10.12688/f1000research.8460.2", 
                        "10.7551/mitpress/9286.001.0001")

# use oadoi_fetch() to get Unpaywall data on those DOIs
my_dois_oa <- roadoi::oadoi_fetch(dois = my_dois,
                                 email = "clarke.iakovakis@okstate.edu")



# print column names
names(my_dois_oa)



# use filter() to overwrite the data frame and keep only items that are available OA
my_dois_oa <- my_dois_oa %>%
  dplyr::filter(is_oa == TRUE)



# print the data frame with best open access location unnested
my_dois_oa %>%
    tidyr::unnest(best_oa_location,
                  names_repair = "universal")