Standardising Research Data (July 2026)

This workshop explains what reproducible research is, why it matters, and what practical steps researchers can take to make their work more reliable and reusable. Using examples drawn from real research practice, it covers common causes of poor reproducibility, including weak data organisation, unclear methods, missing documentation, poor handling of raw data, and a lack of testing and quality assurance.

Participants will work through a framework for standardising research data and workflows: planning and file organisation, tidy data principles, metadata, transparent methods and protocols, documentation, testing for validity and integrity, automation, and preparing data and materials for publication and reuse. The workshop also introduces practical tools and approaches such as folder structures, naming conventions, README files, data dictionaries, data cleaning checks, workflow scripts, repositories, DOIs and ORCID. Participants will leave with a clearer understanding of how to make their own research easier to follow, verify, reproduce and build on.

Please…