ITRN #reproducibility award for scientists, rather than alchemists: a prize for contributions of the past five years (2019 -2023) that are reproducible (i.e., open to the possibility of obtaining the same results from the same premises) and/or replicable https://www.itrn.org/initiatives/reproducibility-awards

📖 Thrilled to see my article on the innovative Nix Package Manager featured in this week's issue of the German Heise c't magazine! Holding the printed version feels surreal and incredibly rewarding.

#Nix is reshaping the way we think about package management with its #declarativity and #reproducibility. In the article, I dive into why Nix is a game-changer and guide readers through building their first project with it, ensuring a seamless and reproducible development environment.

A massive shoutout to the c't editorial team for their impeccable collaboration and support throughout the process. Grateful for the opportunity to share my knowledge and contribute to the tech community.

📸 If you've read it or are interested in Nix, I'd love to hear your thoughts. Feel free to share!

#Nix #NixOS #ctmagazine #techwriting #collaboration #innovation

Beautiful slide deck on reproducible software environments by Ricardo Wurmus presented yesterday at a seminar of the German Research Network (DFN):
https://elephly.net/downies/2023-dfn-slides.pdf

Starts with an acute quote of @khinsen explaining why #reproducibility matters.

#ReproducibleResearch #OpenScience

In this course, you will gain the essential skills to ensure your R projects are not only efficient but also highly reproducible.

Learn how to organize your projects for seamless collaboration using tools like RMarkdown, renv, version control, and more.

If you've worked with R and want to minimize the pain of sharing and reproducing your work, this course with @eliocamp and @paocorrales is perfect for you: https://www.physalia-courses.org/courses-workshops/r-reproducibility/

#Rstats #Reproducibility #DataScience

I’m giving a presentation on how to make #stats / #datascience reproducible using #RStats on 𝟭𝟵 𝗝𝘂𝗹𝘆 for #ReproT, https://rb.gy/21920

it’s based on my book "Building reproducible analytical pipelines with #rstats (https://raps-with-r.dev/)

I’ll quickly walk you through how you can use {renv}, {targets} and #Docker to make your #RStats project reproducible!

#reproducibility #reproducibleresearch