refstudio is an R package that provides a complete toolkit to extract
and process bibliographical references. Its aim is to facilitate
evidence synthesis work and to improve reproducibility in research.
You need to have some familiarity with the R programming
language to use refstudio main functions.
If you don’t feel comfortable with R, we strongly recommend checking Hadley Wickham and Garrett Grolemund’s free and online book R for Data Science and the Coursera course from John Hopkins University Data Science: Foundations using R (free for audit students).
You can install refstudio with:
# install.packages("remotes")
remotes::install_github("giperbio/refstudio")If you use refstudio in your research, please consider citing it. We
put a lot of work to build and maintain a free and open-source R
package. You can find the refstudio citation below.
citation("refstudio")
#>
#> To cite {refstudio} in publications use:
#>
#> Vartanian, D. (2023). {refstudio}: tools to extract and process
#> bibliographical references. R package version 0.0.0.9000.
#> https://giperbio.github.io/refstudio/
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Unpublished{,
#> title = {{refstudio}: tools to extract and process bibliographical references},
#> author = {Daniel Vartanian},
#> year = {2023},
#> url = {https://giperbio.github.io/refstudio/},
#> note = {R package version 0.0.0.9000},
#> }We welcome contributions, including bug reports.
Take a moment to review our Guidelines for Contributing.
Become an refstudio supporter!
Click here to make a
donation. Please indicate the refstudio package in your donation
message.