Working with large volumes of data presents a number of challenges. These are addressed in the free online course Reproducible Research II: Practices and Tools for Managing Computations and Data, available on the FUN MOOC platform. The course provides practical guidance on managing research data, controlling software environments, and automating complex computational analyses.

A range of open-source tools and formats that support reproducibility in scientific work are introduced. Participants will learn how to version and store data using Git Annex, isolate computational environments with Docker, Singularity, and Guix, and automate workflows through tools such as Make and Snakemake. The course also covers common data formats (e.g., FITS, JSON, HDF5), as well as platforms for long-term data and software archiving, including Zenodo and Software Heritage.

The course is currently open. Thanks to its MOOC (Massive Open Online Course) format, it can be completed at any pace until September 10, 2025. Registration remains open until September 3, 2025. The course consists of three standalone modules combining video lectures, reading materials, quizzes, and interactive exercises in a JupyterLab environment. It also includes practical tasks based on real-world scenarios, such as a case study on sunspot detection.

Basic knowledge of the command line, Git, and Python for scientific purposes is recommended. Completion of the previous course, Reproducible Research: Methodological Principles for Transparent Science, is not required, though the two courses are thematically connected. The first course is available in French only.

The course was developed by Inria, the French National Institute for Research in Digital Science and Technology, and is offered via FUN MOOC (France Université Numérique), a public platform providing free online education in collaboration with more than 140 universities and academic institutions worldwide.

More information and course registration can be found here.