Best Practices in Writing Reproducible Code

Open Science practices are becoming central to the way research is conducted. In this workshop, you will learn how to improve the efficiency and reproducibility of your code for yourself and others.

This workshop takes place over two consecutive mornings, and will take you from setting up your project to publishing your code. By the end of the workshop, you will have made steps in making your project more efficient and reproducible, and you will be familiar with good coding practices for research in line with Open Science and FAIR (Findable, Accessible, Interoperable and Reusable) principles.

Workshop Overview

Morning I Topics: Effective Project & Code Structure

In the first half of the workshop, you will:

  • Reorganise your project into a good folder structure
  • Enable version control and collaboration using Git and GitHub
  • Improve the quality of your code and scripts
Morning II Topics: Documentation & Publishing

In the second half of the workshop, you will:

  • Improve the documentation of your code and project
  • Address software dependencies and licensing
  • We will demonstrate how to publish code in a repository and obtain a DOI (digital object identifier) to make your software citable

Planned Dates

To learn more and register, please visit the workshop page for your selected date.

Semester I (2026)

Semester II (2027)

If you have any questions, please contact us via info.rdm@uu.nl.

Prerequisites 

  • You have intermediate knowledge of programming. Examples will primarily address R and Python, but concepts can be applied to most programming languages.
  • You have a project to bring to the workshop. This does not need to be complex; even one script and some associated data will be sufficient — as long as there is room for reworking and improvement.
  • You are part of Utrecht University (UU) or an UU-affiliated organisation (for example, UMC Utrecht).

Still starting out with programming and/or your project? Our workshop Writing Reproducible Manuscripts in R & Python may be interesting for you.

Costs 

There are no costs associated with this workshop. If you register, we count on your attendance so please let us know in advance if you don’t plan to come.

Credits

This workshop has a study load of 8 hours. Your Graduate School can provide ECTS based on this study load.

This workshop is led by the Research Data Management Support team. We are an interdisciplinary group of research engineers, developers, and data specialists from Information & Technology Services and Utrecht University Library, here to support UU researchers.

Learn more
Contact us

Prefer self-paced learning?

Explore our course materials at your own pace, and join us along the way for:

  • Walk-In Hours, Mondays 3-5pm: drop by with any questions or challenges
  • Programming Café, monthly get-togethers with a themed talk and time for programmers of all levels work and share knowledge
Reproducibility Coursebook