R is a language and environment for statistical computing.There are several tools and approaches for interacting with R, but not all are accessible with screen readers.This guide provides an overview of the tools and techniques available to screen reader users across different operating systems, with practical tips and resources to help them navigate the R environment.This guide may not be complete, but I hope it serves as a valuable starting

We are excited to announce the launch of our new project, “Infra Wiss Blogs - Kooperative Informationsinfrastruktur für wissenschaftliche Blogs” funded by the Deutsche Forschungsgemeinschaft (DFG 2023). Blogs have become an indispensable component of digital science communication, serving as a platform for scholarly communication, a diary for documenting research findings in the context of open science, or a showcase for communicating

Summer Meeting of the Editorial Board The re3data.org editorial board was able to get together in person over the summer, meeting for two days in June at the library of the Karlsruhe Institute of Technology (KIT). It was a great opportunity to on-board our new editors and to reconnect with colleagues to focus on updates and improvements to the registry. In addition to the work, the group enjoyed good food and fellowship in the evening.

In August v.12.0 of the InvenioRDM turn-key research data management repository was released, the first long-term support (LTS) release of the open source software since January 2023. This release enabled the migration of the Rogue Scholar infrastructure to the InvenioRDM platform, a process that will take the next four months. Deployment The first stage of the migration was setting up the InvenioRDM production infrastructure.

Dear rOpenSci friends, it’s time for our monthly news roundup! You can read this post on our blog.Now let’s dive into the activity at and around rOpenSci! rOpenSci HQ Community call: Navigating the R ecosystem using R-Universe! On Tuesday, 24 September 2024 16:00 UTC (no RSVP needed), join us to learn more about R-Universe and how you can use it to improve your R package development workflow.

Image was created with the assistance of AI. By Michelle Barker, Kim Hartley, Daniel S. Katz, Richard Littauer, Qian Zhang, Shurui Zhou, Jyoti Bhogal August 2024 [This blog post has been cross-posted by the Netherlands eScience Center, Software Sustainability Institute, and US-RSE.] Abstract This position paper provides a statement on the criticality of research software in artificial intelligence (AI)-driven research and makes

(Please cite this post as https://doi.org/10.59350/rjt2m-2hy19) A few things recently have made me think about how we support the core work of maintaining research software and supporting its users. I was interviewed by Georgia Iacovou for her report, “The state of the open source ecosystem &

Vendredi 9 août, l’équipe de Zotero annonçait la sortie officielle de Zotero 7 sur son blog: https://www.zotero.org/blog/zotero-7/. Nous avons traduit ce billet en français.

Introduction Let’s be honest, being a statistician or a scientist isn’t just about crunching numbers all day . It’s more like being a detective, a problem solver, and yeah, throwing in some math for good measure. When we get into non-linear models , things really start to get interesting. We’re not just drawing straight lines anymore;

R packages, like any software, require maintenance. Package maintenance includes: Fixing bugs when discovered. Adapting to updates in package dependencies. Providing some level of user and contributor support. When desired, refactoring code or adding new functionality. Without maintenance efforts a package is at risk of losing its value. Yet, maintaining a package for years or even decades can be challenging as it is time consuming.