Reusability of Scientific Data - for Matter

12.11.2026

Ensuring that research data can be reused beyond its original context is a key objective of the FAIR data principles. Reusable data requires clear documentation, persistent identifiers, and appropriate licensing practices.

This course focuses on the “R” in FAIR and explores how these elements support long-term usability of experimental research data. Participants will develop a structured understanding of data reusability and learn practical steps to improve reuse in their own research workflows – because context matters.

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

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.

Prerequisites
No prior knowledge is required.

At a Glance
• Date: 12 November 2026
• Time: 9:30 AM–2:30 PM (CET)
• Format: Online (Zoom)
• Trainer: Özlem Özkan, HMC Hub Matter – Helmholtz-Zentrum Berlin (HZB)
• Registration: https://events.hifis.net/event/3688

Joint HIDS Course Portfolio
Selected HMC trainings are part of the joint HIDS Course Portfolio within the Helmholtz Information & Data Science Framework (HIDS). The portfolio is jointly organized by its five platforms Helmholtz AI, HMC, Helmholtz Imaging, HIDA, and HiFIS. It provides structured learning pathways across all experience levels and is free of charge for Helmholtz employees. All courses are held in English.

Further information and the full course overview are available in the HIDS Data Course Portfolio and all HMC courses via the HMC training overview page.