Lattes is the largest platform of academic CVs in Brazil. It holds information about the academic work of all Brazilian scholars, including the institutions of their degrees, current employer, field of work, publication metadata, and much more. It is a unique and reliable source of information for bibliometric studies.
Package GetLattesData provides a simple API to read the XML files exported by the Lattes platform into tidy dataframes, and to enrich publications with Qualis (the Brazilian journal ranking) and SJR indicators.
Some studies that have used this data:
- Is predatory publishing a real threat? Evidence from a large database study. Scientometrics
- The Brazilian scientific output published in journals: A study based on a large CV database. Journal of Informetrics
- The researchers, the publications and the journals of Finance in Brazil: An analysis based on resumes from the Lattes platform. Brazilian Review of Finance
- Análise do Perfil dos Acadêmicos e de suas Publicações Científicas em Administração (in Portuguese). RAC
The package is available in CRAN:
install.packages('GetLattesData')You can also install the development version from GitHub:
# install.packages('devtools')
devtools::install_github('msperlin/GetLattesData')GetLattesData requires R >= 4.1.0.
Due to a captcha wall on the Lattes website, GetLattesData no longer downloads CVs automatically. To use the package you must:
- Open the researcher's CV on Lattes.
- Click the XML button in the top-right corner of the page.
- Solve the captcha and save the resulting
.zipfile locally. - Read it with the functions below.
Two example CVs are shipped with the package. Replace them with the files you downloaded.
gld_read_zip2() parses one Lattes .zip file and returns a list of tibbles:
library(GetLattesData)
f_in <- system.file('extdata/3262699324398819.zip', package = 'GetLattesData')
my_l <- gld_read_zip2(f_in)
names(my_l)
#> [1] "info" "course_bachelors" "course_msc" "course_phd"
#> [5] "pos_doc" "published_papers" "accepted_papers" "books"
#> [9] "supervisions" "at_prof" "projects" "coauthors"
#> [13] "conferences" "awards"gld_get_lattes_data_from_zip() reads a vector of .zip files, combines the results, and enriches the publications with Qualis and SJR:
f_in <- system.file(
c('extdata/3262699324398819.zip', 'extdata/8373564643000623.zip'),
package = 'GetLattesData'
)
l_out <- gld_get_lattes_data_from_zip(
zip.files = f_in,
field.qualis = 'ADMINISTRAÇÃO PÚBLICA E DE EMPRESAS, CIÊNCIAS CONTÁBEIS E TURISMO'
)
names(l_out)
l_out$tpesq # researchers
l_out$tpublic.published # published papers (+ qualis, SJR, H.SJR)
l_out$tpublic.accepted # accepted papersfield.qualis must match a Qualis area exactly (see the Qualis table from CAPES/Sucupira). If you do not need Qualis, omit the argument.
gld_read_zip2() returns a list with the following elements:
| Element | Contents |
|---|---|
info |
researcher general information |
course_bachelors, course_msc, course_phd |
academic degrees |
pos_doc |
post-doctoral training |
published_papers, accepted_papers |
journal articles |
books |
published/organized books |
supervisions |
completed supervisions (MSc, PhD, and others) |
at_prof |
professional activities / employment |
projects |
research and extension projects |
coauthors |
co-authors of published papers |
conferences |
conference papers |
awards |
awards and titles |
Every table includes the researcher's nome_completo and the source id_file, so results from several CVs can be safely combined.
The older gld_get_lattes_data_from_zip() returns the same information with different names (tpesq, tpublic.published, tpublic.accepted, tsupervisions, tbooks, tconferences, t_atprof, tprojects, tcoauthors) and adds qualis, SJR and H.SJR columns to the papers.
If you use GetLattesData in academic work, please cite the package:
citation('GetLattesData')GPL-2. See LICENSE.
Bug reports and feature requests are welcome at https://github.com/msperlin/GetLattesData/issues.