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 in the road of becoming professional data steward.
The first meeting will be on the 9th of Feb at 10 am in Zoom (see link below)
- Tuesday 10.15 - 12.00, online via Zoom, log in to see the link
- Monday 10.15 - 12.00, online via Zoom, log in to see the link
- Lecturer: Priit Adler
- Slack: (request access)
- 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 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
It is possible to earn 100 points during the course (more if completing bonus tasks). Homeworks are worth 50 points and 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 for bonus tasks.