Foundational introduction to scientific metadata and machine-readable research data annotation.
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.
Structured metadata plays a central role in enabling transparent, interoperable, and reusable research data. In many research workflows, metadata provides the context that allows datasets to be interpreted, shared, and reused beyond their original project.
This course introduces the core principles of scientific metadata and explains how structured, machine-readable metadata supports research quality and visibility. Participants will gain both conceptual understanding and practical orientation in metadata frameworks and JSON-based annotation.
Learning goals
By the end of the course, participants will be able to:
- explain the role of structured metadata in research quality and reuse
- describe how metadata frameworks support FAIR data principles
- create basic machine-readable metadata records using JSON
Course date
Register now: 7-8 July 2026
For more information on how to register, please follow the link on the course date.
Prerequisites
No prior knowledge needed.
Target group
This course is designed for researchers within Helmholtz Hub Health. It is particularly relevant for PhD students, early-career researchers, and postdoctoral researchers working with research datasets.
This course is free of charge.
