Reproductible Research II : Pratiques et outils pour gérer les calculs et les données

Following the success of the MOOC Reproducible research: methodological principles for transparent science, the authors continue exploring reproducibility with a focus on massive data and complex calculations. These two MOOCs complement each other and offer a coherent training program on the subject.

In this second MOOC Reproducible Research II: Practices and tools for managing computations and.., you will learn:

• how to manage large datasets and complex computations in controlled software environments
  • formats such as JSON, FITS, and HDF5
  • platforms like Zenodo and Software Heritage
  • tools like git-annex, Docker, Singularity, Guix, make, and Snakemake,
• how to integrate them in a real-life use case: a sunspot detection study.

Authors: Arnaud Legrand (Computer science researcher, CNRS/LIG, Inria, UGA), Christophe Pouzat (Neurophysiologist, CNRS/MAP5 Univ. Paris Descartes) and Konrad Hinsen (Biophysicist, CNRS, Centre de biophysique moléculaire, Soleil).

Technical and engineering support: Matthieu Simonin (research engineer, Inria Rennes), Ludovic Courtès (research engineer, Inria Bordeaux) and Kim tâm Huynh (research engineer, Inria Paris).

Partners: with the support of Fonds national de la science ouverte

ℹ️ Useful information

Open for free from 5 May to 31 December 2026 Language: English Target audience: PhD’ s, researchers, master students, teachers, engineers from all disciplines Effort: 35 hours, at your own pace Certification: Open Badge delivered by FUN, on request

🔗 Registration here