| Votes | By | Price | Discipline | Year Launched |
| rOpenSci | FREE OPEN SOURCE | Interdisciplinary |
Description
Features
Offers
Reviews
rOpenSci is a non-profit organization that funds and builds open tools for open science, especially around the R language ecosystem. It supports open research software, data access, reproducible workflows, and a community of scientists, developers, and maintainers. Their work covers software review, infrastructure, training & mentorship, multilingual publishing, etc.
Key Activities & Programs
- Software Peer Review
- rOpenSci runs a peer-review process for R packages: combining academic peer review + code review via GitHub.
- The aim: improve package quality, enforce best practices, build community collaboration.
- There is a publicly viewable list of “open reviews”.
- R-Universe Platform
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- A next-generation platform for discovering, developing, and publishing R packages and repositories.
- It lets individuals, orgs or consortia manage their own collections/repositories at scale.
- Champions Program
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- A program for people contributing to open-source, open-science in local communities — helping them become “champions”.
- Includes mentoring, community support, being part of broader global network.
- Multilingual Publishing
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- They recognise the importance of non-English users and are working to translate their materials and tools (guides, documentation) into languages like Spanish, Portuguese, Turkish, etc.
- Community Engagement & Resources
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- Ambitious community calls, discussion forums, events.
- Many categories of packages: data access, data extraction, visualization, geospatial, HTTP tools, statistics, taxonomy, etc.
Why It Matters
- In research, reproducibility and open access are increasingly important. rOpenSci’s tools help make science more transparent, accessible, and efficient.
- For anyone working in R or data science (in academia, government, industry), using vetted open-source tools means less reinvention, more reliability.
- Building a community around open-software ensures the tools keep improving, adapting, and meeting users’ needs.
- Their peer-review model raises the bar for research-software quality (not just code, but documentation, testing, maintenance).
- Multilingual efforts broaden access beyond English-speaking researchers — important for global science equity.
Some of the popular tools are:
Taxize: A “taxonomic toolbelt” for R: it allows you to query many taxonomic databases (scientific & common names), verify species names, fetch upstream/downstream taxonomic hierarchies, synonyms, etc.
Rgbif: An R package to interface with the Global Biodiversity Information Facility (GBIF) API — it allows you to search and retrieve biodiversity occurrence data (species occurrences, counts, metadata) from GBIF.
Skimr: A tool for compact, flexible summary statistics in R: it gives a clean summary of data frames/vectors, supports custom summaries and “spark” graphs in console.
magik: Bindings in R for the ImageMagick library — supports many image formats (png, jpeg, tiff, pdf), and operations like rotate, scale, crop, blur, flip, animation.
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