Working together to push science forward
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The R package ecosystem now contains more than 10K packages, and several flagship packages belong under the rOpenSci suite. Some of these are: magick for image manipulation, plotly for interactive plots, and git2r for interacting with git. rOpenSci is a community of people making software to facilitate open and reproducible science/research. While the rOpenSci team continues to develop and maintain core infrastructure packages, an increasing number of packages in our suite are contributed by members of the extended R community....
It all started January 26th this year when I signed up to volunteer as a reviewer for R packages submitted to rOpenSci. My main motivation for wanting to volunteer was to learn something new and to contribute to the R open source community. If you are wondering why the people behind rOpenSci are doing this, you can read How rOpenSci uses Code Review to Promote Reproducible Science. Three months later I was contacted by Maëlle Salmon asking whether I was interested in reviewing the R package patentsview for rOpenSci....
We have started working on a new rOpenSci package called writexl. This package wraps the very powerful libxlsxwriter library which allows for exporting data to Microsoft Excel format. The major benefit of writexl over other packages is that it is completely written in C and has absolutely zero dependencies. No Java, Perl or Rtools are required. 🔗 Getting Started The write_xlsx function writes a data frame to an xlsx file....
The new rOpenSci spelling package provides utilities for spell checking common document formats including latex, markdown, manual pages, and DESCRIPTION files. It also includes tools especially for package authors to automate spell checking of R documentation and vignettes. 🔗 Spell Checking Packages The main purpose of this package is to quickly find spelling errors in R packages. The spell_check_package() function extracts all text from your package manual pages and vignettes, compares it against a language (e....
At rOpenSci, we create and curate software to help scientists with the data life cycle. These tools access, download, manage, and archive scientific data in open, reproducible ways. Early on, we realized this could only be a community effort. The variety of scientific data and workflows could only be tackled by drawing on contributions of scientists with field-specific expertise. With the community approach came challenges. How could we ensure the quality of code written by scientists without formal training in software development practices?...
Happy rOpenSci users can be found at