Our packages are carefully vetted, staff- and community-contributed R software tools that in particular lower barriers to working with local and remote scientific data sources. Browse use cases and read our blog to learn how to use specific packages or contribute to their improvement.
Curious about contributing your package? See our Software Peer Review page for details. We welcome volunteers to review packages submitted to our open peer review process.
Below are some highlighted categories of packages. If you are not too sure where to look, use the page with all packages. In any case, all packages pages have a search bar. If a tool for your need seems missing, feel free to post on our forum.
Workflow Tools for Your Code and Data
View all packagesGet Data from the Web
View all packagesConvert and Munge Data
View all packagesDocument and Release Your Data
View all packagesVisualize Data
View all packagesWork with Databases From R
View all packagesAccess, Manipulate, Convert Geospatial Data
View all packagesInteract with Web Resources
View all packagesUse Image & Audio Data
View all packagesAnalyze Scientific Papers (and Text in General)
View all packagesSecure Your Data and Workflow
View all packagesHandle and Transform Taxonomic Information
View all packagesOur suite of packages is comprised of contributions from staff engineers and the wider R community via a transparent, constructive and open review process utilising GitHub's open source infrastructure.
Find out moreWe combine academic peer reviews with production software code reviews to create a transparent, collaborative & more efficient review process
View open reviewsBased on best practices of software development and standards of R, it’s applications and user base.
View DocumentationOur diverse community of academics, data scientists and developers provide a platform for shared learning, collaboration and reporoducible science
Review for rOpenSciWe welcome both code and non-code contributions. Read our Contributing Guide to learn how.