Dive deep into the FAIR data principles—Findable, Accessible, Interoperable, and Reusable—and learn how to interpret and apply them across different disciplines and data types. This module addresses both the theoretical foundations and the practical challenges of implementing FAIR, extending the discussion to new frontiers such as software and AI models.
Key Topics
- In-depth analysis of FAIR principles
- Structure of Data Management Plans
- Integration of FAIR in data management plans and research workflows
Learning Outcomes
- Critically interpret each FAIR principle and understand their technical and conceptual implications
- Integrate FAIR principles into planning, execution, and publication of research outputs
