This module covers key concepts, tools and methods to implement FAIR-by-design pipelines to manage, curate, and preserve research data in compliance with FAIR principles.
Key Topics
- Ontology, data model and metadata schema
- Data ingestion from different sources, Data harmonization and data formats
- Interacting with data repository
- ‘Real world’ data interoperability: main challenges and examples
- Exploring FAIR data as Fully AI Ready
- Brief introduction to Data Policy and Data Governance
Learning Outcomes
- Apply metadata standards to ensure interoperability
- Use curation tools to prepare datasets for sharing and preservation
- Automate routine data management tasks to improve efficiency
