Contents in Detail
Module 1: Basics of Research Data Management and Open Science
Introduction to:
- Research data management
- Good scientific practice
- Open Access, Open Science, Open Data
- Cost estimation and financing models
- Legal and ethical aspects
- Role and Tasks of Data Stewards
Module 2: Basics of IT and Data Science
Introduction to:
- Data science and data-driven research
- Machine learning
- Database systems
Basics of programming (based on the Carpentries curriculum):
- Unix Shell
- Git and GitHub
- Working with Python
Module 3: FAIR Research Data in the Life Cycle
Research data life cycle:
- Project management and funding landscape
- Data management plans (DMPs)
- Data organization and curation
- Data visualization
- Metadata and research data documentation (incl. persistent identifiers, ontologies, etc.)
- Data security and storage
- Repository management and long-term preservation
- Interoperability and data migration
- Data reuse (incl. legal requirements)
Discipline-specific approaches to data stewardship in the:
- Natural and life sciences
- Humanities
- Social sciences
- Technical sciences
Module 4: Research Data Management Support
- Developing research data management support services
- Designing and delivering training
- Conducting needs-assessments and requirements engineering
Modul 5: Data Stewardship in Practice: Project Work
- Individual or group project applying the acquired skills and knowledge to data stewardship practice