Data Stewardship – Module 2

Building on the theoretical foundations of Module 1, Module 2 focuses on the practical aspects of research data management. The module consists of four interactive workshops, complemented by guest lectures, that guide participants through concrete steps of handling research data. Topics include science evaluation, data collection and storage, FAIR principles, repository selection, and data archiving. By actively working with real examples, participants will not only learn best practices, but also practice creating their own data records in a repository.

Upon completion of Module 2, participants should be able to:
- Identify relevant scientific databases, citation tools, metrics, and licences related
to their research.
- Organize and describe their data according to FAIR principles and best
practices of research data management.
- Develop and critically assess a data management plan.
- Select an appropriate repository and prepare their data, including metadata and
documentation, for sharing and archiving.
- Apply acquired knowledge in practice by depositing their own dataset in a
repository.

Entry requirements for the course: English language level B1+, Certificate from Data Stewardship – Module 1

Requirements for course completion: Final task in LMS and 75% attendance at workshops.

Applications: http://czv.vsb.cz/kurzy

1. AI Tools in Science and Research
- Examples of selected AI tools for research
- Strengths and weaknesses: Where AI helps and where it fails
- Data or literature: Data visualizations and analysis using AI
- Mini-exercises with trial data and AI tools
2. Protecting CZ Science: Rules anyone should follow
- Web of Science/Scopus indicators in correlation with VSB and projects needs
- Open Science: Financing, preprint creation, or embargo?
- DOAJ and Open Review journals: CZ way of sustainability
- Journal selection – higher citation or better journal?
3. FAIR Data Trusted Repository
- FAIR principles: Examples of good/bad practice
- README files following Dublin Core
- Data versioning & Workflow via communities in Zenodo (other repositories)
- Recommended practices within Open Science
4. Data Management Plan
- Essential tools to cope with DMP
- Implications FAIR to be “...as closed as necessary”
- Horizon Europe Quest: Deep learning with researchers
- DMP as a strategic living document in a project
5. Summary and final task in LMS"