Computational Reproducibility: A Primer from UKRN

This primer introduces the key concepts and challenges of computational reproducibility, the ability to obtain the same results from the same data and computational procedures. It is intended for anyone involved in research that uses a computer at any stage of the process, regardless of technical background.

The document outlines the aspects of reproducibility that depend on computational tools, illustrating how issues such as ambiguous method descriptions, missing resources, changing software versions, and unavailable packages can make analyses difficult or impossible to reproduce. It provides clear, practical guidance on how to mitigate these risks and adopt more robust, transparent research practices.

Readers are encouraged to deepen their understanding of the tools and methods they use, and to consider what level of reproducibility is appropriate for their work. The primer emphasises that reproducibility does not guarantee correctness, but it does enable others to understand and evaluate the work, supporting cumulative knowledge building. It also introduces the FAIR principles, Findable, Accessible, Interoperable, and Reusable, as a useful framework for assessing computational tools and workflows.

No prior technical expertise is required, and the primer includes curated references for those wishing to explore the topic further.