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.
Prerequisites
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).
Installation
You can install refstudio with:
# install.packages("remotes")
remotes::install_github("giperbio/refstudio")Citation
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 @Unpublished{,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},
#> }Contributing
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.
