Focused introduction to the FAIR “R” principle and practical data reusability strategies in the Matter domain.
This course is offered by HMC in cooperation with HIDA
HMC
The Helmholtz Metadata Collaboration (HMC) promotes the qualitative enrichment of research data by means of metadata – and implements this approach across the whole organization.
HMC develops and implements novel concepts and technologies for a sustainable handling of research data through high-quality metadata. Its main goal is to make the depth and breadth of research data produced by Helmholtz Centres findable, accessible, interoperable and reusable (FAIR) for the whole science community.
This course explores the reusability dimension of the FAIR principles and provides practical guidance on documentation, licensing, and persistent identifiers. Participants learn how to improve the long-term usability of research data in experimental research contexts.
Learning goals
By the end of the course, participants will be able to:
- explain what data reusability means within the FAIR framework
- identify documentation requirements that support reuse
- select appropriate licenses for research data
- apply practical steps to enhance data reusability
This course was developed by HMC in collaboration with Helmholtz AI.
Course date
Register now:
For more information on how to register, please follow the link on the course date.
Note: The training on 21 May 2026 will also feature two invited talks:
- “Reusability in AI” by Dr. Till Korten (Helmholtz AI)
- “Reusability in Matter” by Dr. Brian Richard Pauw (BAM)
Prerequisites
No prior knowledge needed.
Target group
This course is aimed at researchers in the Research Field Matter. It is particularly relevant for PhD students and postdoctoral researchers working with experimental or measurement data.
This course is free of charge.
The Data Science Course Portfolio
This course is part of the Data Science Course Portfolio, curated by the five Helmholtz Information & Data Science Platforms - Helmholtz AI, Helmholtz Imaging, HIDA, HIFIS, HMC. Find out more on the Course Portfolio here.
