Course info
Good data management strategy ensures the safe storage and protection of researchers' intellectual capital. It makes it easier to meet the demands of funders and publishers in respect of research data. Well-curated and documented research data is more comfortable to reuse by other researchers, ensuring better exposure of scientific work and the replicability of the analysis results.
We learn FAIR's principles (Findable, Accessible, Interoperable, Reusable) data during the course. Introduce why is data management plan necessary and learn how to compile one for a project. Introduce the best practices and principles of data management.
We will also learn the role of Data Steward on an institutional level, their responsibilities, tasks and activities.
This course provides the first steps on the road to becoming a professional data steward.
Schedule
The first meeting will be on the 6th of Feb at 10 am in Delta, room 2047
- Lectures:
- Monday 10.15 - 12.00, log in to see zoom link
- Practicals/seminars:
- Tuesday 12.15 - 14.00,
To connect zoom session, one is required first to log in to zoom (authenticated zoom users only)
Contacts
- Lecturer: Priit Adler
Learning objectives
- Student is aware of the principle toosĺs for data management
- Students can convey the importance and principles of data management to their peers
- Students know how to compile a data management plan for a project
- knowledge of the components of a data management plan
- FAIR (Findable, Accessible, Interoperable, Reusable) principle
- Student is aware of the basic principles of data mining
- Student knows the tasks and activities of Data Steward on a project and organisation level
Grading
It is possible to earn 100 points during the course (more if completing bonus tasks). Homeworks are worth 50 points, and the exam another 50 points.
To pass the course you need to get at least 51 points.
Bonus points are granted for active participation in seminars and practicals and bonus tasks.