fulltext package - RDocumentation

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

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, and via Spark-R to handle especially large jobs
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')

Extraction tools

If you want to use ft_extract() function, it currently has two options for how to extract text from PDFs: xpdf and ghostscript.

xpdf installation: See http://www.foolabs.com/xpdf/download.html for instructions on how to download and install xpdf. For OSX, you an also get xpdf via Homebrew with brew install xpdf. Apparently, you can optionally install Poppler, which is built on xpdf. Get it at http://poppler.freedesktop.org/
ghostscript installation: See http://www.ghostscript.com/doc/9.16/Install.htm

for instructions on how to download and install ghostscript. For OSX, you an also get ghostscript via https://github.com/Homebrew/homebrew-core/blob/master/Formula/ghostscript.rb with brew install gs.

Search

ft_search() - get metadata on a search query.

ft_search(query = 'ecology', from = 'plos')
#> Query:
#>   [ecology] 
#> Found:
#>   [PLoS: 33966; BMC: 0; Crossref: 0; Entrez: 0; arxiv: 0; biorxiv: 0; Europe PMC: 0] 
#> Returned:
#>   [PLoS: 10; BMC: 0; Crossref: 0; Entrez: 0; arxiv: 0; biorxiv: 0; Europe PMC: 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] 3 
#> [IDs] ID_27439703 ID_27439360 ID_27434666 ...

Or pass in DOIs directly

ft_links(res1$entrez$data$doi, from = "entrez")
#> <fulltext links>
#> [Found] 3 
#> [IDs] ID_27439703 ID_27439360 ID_27434666 ...

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.0063114" "10.1371/journal.pone.0039479"
#> [3] "10.1371/journal.pone.0003940" "10.1371/journal.pcbi.0030082"
#> [5] "10.1371/journal.pone.0051856"
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.0063114 Public Library of ScienceSan Francisco, USA
#> 2 10.1371/journal.pone.0039479 Public Library of ScienceSan Francisco, USA
#> 3 10.1371/journal.pone.0003940 Public Library of ScienceSan Francisco, USA
#> 4 10.1371/journal.pcbi.0030082 Public Library of ScienceSan Francisco, USA
#> 5 10.1371/journal.pone.0051856 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
#> 1 10.1371/journal.pone.0063114 Public Library of ScienceSan Francisco, USA
#> 2 10.1371/journal.pone.0039479 Public Library of ScienceSan Francisco, USA
#> 3 10.1371/journal.pone.0003940 Public Library of ScienceSan Francisco, USA
#> 4 10.1371/journal.pcbi.0030082 Public Library of ScienceSan Francisco, USA
#> 5 10.1371/journal.pone.0051856 Public Library of ScienceSan Francisco, USA
#>   permissions.copyright.year permissions.copyright.holder
#> 1                       2013              Schaafsma et al
#> 2                       2012            Novoseltsev et al
#> 3                       2008                Luchman et al
#> 4                       2007                Puccini et al
#> 5                       2012              Ambrosini et al
#>   permissions.license_url
#> 1                    <NA>
#> 2                    <NA>
#> 3                    <NA>
#> 4                    <NA>
#> 5                    <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))
#> Error in ft_get_si.character("10.6084/m9.figshare.979288", 2): '...' used in an incorrect context
head(catching.crabs)
#> Error in head(catching.crabs): object 'catching.crabs' not found

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 various pdf to text parsing backends

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

Using ghostscript

(res_gs <- ft_extract(pdf, "gs"))
#> <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

Using xpdf

(res_xpdf <- ft_extract(pdf, "xpdf"))
#> <document>/Users/sacmac/github/ropensci/fulltext/inst/examples/example2.pdf
#>   Pages: 10
#>   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_xpdf <- ft_extract_corpus(paths, "xpdf"))
#> $meta
#>           names                           class
#> 1 content, meta PlainTextDocument, TextDocument
#> 2 content, meta PlainTextDocument, TextDocument
#> 3 content, meta PlainTextDocument, TextDocument
#> 4 content, meta PlainTextDocument, TextDocument
#> 
#> $data
#> <<VCorpus>>
#> Metadata:  corpus specific: 0, document level (indexed): 0
#> Content:  documents: 4
#> 
#> attr(,"class")
#> [1] "xpdf"

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>
#>  .....

Installation

Extraction tools

Search

Get full text links

Get full text

Extract chunks

Supplementary materials

Cache

Extract text from PDFs

Meta

Copy Link

Version

Install

Monthly Downloads

Version

License

Issues

Pull Requests

Stars

Forks

Repository

Maintainer

Last Published

Functions in fulltext (0.1.8)