_____     .__  .__   __                   __
_/ ____\_ __|  | |  |_/  |_  ____ ___  ____/  |_
\   __\  |  \  | |  |\   __\/ __ \\  \/  /\   __\
 |  | |  |  /  |_|  |_|  | \  ___/ >    <  |  |
 |__| |____/|____/____/__|  \___  >__/\_ \ |__|
                                \/      \/

Get full text articles from (almost) anywhere

rOpenSci has a number of R packages to get either full text, metadata, or both from various publishers. The goal of fulltext is to integrate these packages to create a single interface to many data sources.

fulltext makes it easy to do text-mining by supporting the following steps:

• Search for articles
• Fetch articles
• Get links for full text articles (xml, pdf)
• Extract text from articles / convert formats
• Collect bits of articles that you actually need
• Download supplementary materials from papers

Additional steps we hope to include in future versions:

• Analysis enabled via the tm package and friends
• Visualization

Data sources in fulltext include:

• Crossref - via the rcrossref package
• Public Library of Science (PLOS) - via the rplos package
• Biomed Central
• arXiv - via the aRxiv package
• bioRxiv - via the biorxivr package
• PMC/Pubmed via Entrez - via the rentrez package
• Many more are supported via the above sources (e.g., Royal Society Open Science is available via Pubmed)
• We will add more, as publishers open up, and as we have time...See the master list here

Authorization: A number of publishers require authorization via API key, and some even more draconian authorization processes involving checking IP addresses. We are working on supporting all the various authorization things for different publishers, but of course all the OA content is already easily available.

We'd love your feedback. Let us know what you think in the issue tracker

Article full text formats by publisher: https://github.com/ropensci/fulltext/blob/master/vignettes/formats.Rmd

Installation

Stable version from CRAN

install.packages("fulltext")

Development version from GitHub

devtools::install_github("ropensci/fulltext")

Load library

library('fulltext')

Search

ft_search() - get metadata on a search query.

ft_search(query = 'ecology', from = 'plos')
#> Query:
#>   [ecology] 
#> Found:
#>   [PLoS: 39041; BMC: 0; Crossref: 0; Entrez: 0; arxiv: 0; biorxiv: 0; Europe PMC: 0; Scopus: 0; Microsoft: 0] 
#> Returned:
#>   [PLoS: 10; BMC: 0; Crossref: 0; Entrez: 0; arxiv: 0; biorxiv: 0; Europe PMC: 0; Scopus: 0; Microsoft: 0]

Get full text links

ft_links() - get links for articles (xml and pdf).

res1 <- ft_search(query = 'ecology', from = 'entrez', limit = 5)
ft_links(res1)
#> <fulltext links>
#> [Found] 1 
#> [IDs] ID_28724921 ...

Or pass in DOIs directly

ft_links(res1$entrez$data$doi, from = "entrez")
#> <fulltext links>
#> [Found] 1 
#> [IDs] ID_28724921 ...

Get full text

ft_get() - get full or partial text of articles.

ft_get('10.1371/journal.pone.0086169', from = 'plos')
#> <fulltext text>
#> [Docs] 1 
#> [Source] R session  
#> [IDs] 10.1371/journal.pone.0086169 ...

Extract chunks

library("rplos")
(dois <- searchplos(q = "*:*", fl = 'id',
   fq = list('doc_type:full',"article_type:\"research article\""), limit = 5)$data$id)
#> [1] "10.1371/journal.pone.0003649" "10.1371/journal.pone.0057589"
#> [3] "10.1371/journal.pone.0003616" "10.1371/journal.pone.0003505"
#> [5] "10.1371/journal.pone.0003677"
x <- ft_get(dois, from = "plos")
x %>% chunks("publisher") %>% tabularize()
#> $plos
#>                                     publisher
#> 1 Public Library of ScienceSan Francisco, USA
#> 2 Public Library of ScienceSan Francisco, USA
#> 3 Public Library of ScienceSan Francisco, USA
#> 4 Public Library of ScienceSan Francisco, USA
#> 5 Public Library of ScienceSan Francisco, USA

x %>% chunks(c("doi","publisher")) %>% tabularize()
#> $plos
#>                            doi                                   publisher
#> 1 10.1371/journal.pone.0003649 Public Library of ScienceSan Francisco, USA
#> 2 10.1371/journal.pone.0057589 Public Library of ScienceSan Francisco, USA
#> 3 10.1371/journal.pone.0003616 Public Library of ScienceSan Francisco, USA
#> 4 10.1371/journal.pone.0003505 Public Library of ScienceSan Francisco, USA
#> 5 10.1371/journal.pone.0003677 Public Library of ScienceSan Francisco, USA

Use dplyr to data munge

library("dplyr")
x %>%
 chunks(c("doi", "publisher", "permissions")) %>%
 tabularize() %>%
 .$plos %>%
 select(-permissions.license)
#>                            doi                                   publisher permissions.copyright.year permissions.copyright.holder permissions.license_url
#> 1 10.1371/journal.pone.0003649 Public Library of ScienceSan Francisco, USA                       2008           Rajagovindan et al                    <NA>
#> 2 10.1371/journal.pone.0057589 Public Library of ScienceSan Francisco, USA                       2013                   Dane et al                    <NA>
#> 3 10.1371/journal.pone.0003616 Public Library of ScienceSan Francisco, USA                       2008                Bandera et al                    <NA>
#> 4 10.1371/journal.pone.0003505 Public Library of ScienceSan Francisco, USA                       2008                Brodeur et al                    <NA>
#> 5 10.1371/journal.pone.0003677 Public Library of ScienceSan Francisco, USA                       2008              Kuparinen et al                    <NA>

Supplementary materials

Grab supplementary materials for (re-)analysis of data

ft_get_si() accepts article identifiers, and output from ft_search(), ft_get()

catching.crabs <- read.csv(ft_get_si("10.6084/m9.figshare.979288", 2))
head(catching.crabs)
#>   trap.no. length.deployed no..crabs
#> 1        1          10 sec         0
#> 2        2          10 sec         0
#> 3        3          10 sec         0
#> 4        4          10 sec         0
#> 5        5          10 sec         0
#> 6        1           1 min         0

Cache

When dealing with full text data, you can get a lot quickly, and it can take a long time to get. That's where caching comes in. And after you pull down a bunch of data, if you do so within the R session, you don't want to lose that data if the session crashes, etc. When you search you will be able to (i.e., not ready yet) optionally cache the raw JSON/XML/etc. of each request locally - when you do that exact search again we'll just give you the local data - unless of course you want new data, which you can do.

ft_get('10.1371/journal.pone.0086169', from='plos', cache=TRUE)

Extract text from PDFs

There are going to be cases in which some results you find in ft_search() have full text available in text, xml, or other machine readable formats, but some may be open access, but only in pdf format. We have a series of convenience functions in this package to help extract text from pdfs, both locally and remotely.

Locally, using code adapted from the package tm, and two pdf to text parsing backends

pdf <- system.file("examples", "example2.pdf", package = "fulltext")

(res <- ft_extract(pdf))
#> <document>/Users/sacmac/github/ropensci/fulltext/inst/examples/example2.pdf
#>   Title: pone.0107412 1..10
#>   Producer: Acrobat Distiller 9.0.0 (Windows); modified using iText 5.0.3 (c) 1T3XT BVBA
#>   Creation date: 2014-09-18

Or extract directly into a tm Corpus

paths <- sapply(paste0("example", 2:5, ".pdf"), function(x) system.file("examples", x, package = "fulltext"))
(corpus <- ft_extract_corpus(paths))
#> $meta
#> data frame with 0 columns and 0 rows
#> 
#> $data
#> <<SimpleCorpus>>
#> Metadata:  corpus specific: 1, document level (indexed): 0
#> Content:  documents: 4
#> 
#> attr(,"class")
#> [1] "ft_extract"

Extract pdf remotely on the web, using a service called PDFX

pdf5 <- system.file("examples", "example5.pdf", package = "fulltext")
pdfx(file = pdf5)

#> $meta
#> $meta$job
#> [1] "34b281c10730b9e777de8a29b2dbdcc19f7d025c71afe9d674f3c5311a1f2044"
#>
#> $meta$base_name
#> [1] "5kpp"
#>
#> $meta$doi
#> [1] "10.7554/eLife.03640"
#>
#>
#> $data
#> <?xml version="1.0" encoding="UTF-8"?>
#> <pdfx xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:noNamespaceSchemaLocation="http://pdfx.cs.man.ac.uk/static/article-schema.xsd">
#>   <meta>
#>     <job>34b281c10730b9e777de8a29b2dbdcc19f7d025c71afe9d674f3c5311a1f2044</job>
#>     <base_name>5kpp</base_name>
#>     <doi>10.7554/eLife.03640</doi>
#>   </meta>
#>    <article>
#>  .....

Contributors

• Scott Chamberlain http://github.com/sckott
• Will Pearse https://github.com/willpearse

Meta

• Please report any issues or bugs.
• License: MIT
• Get citation information for fulltext: citation(package = 'fulltext')
• Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.