Today, many scientific disciplines are data-intensive: They produce a lot of research data, but also need a lot of data to answer their central questions.
Thus, proper management of research data is becoming more and more crucial. It is necessary to support reproducibility of scientific results, to be able to build on work by others - or simply to answer questions based on existing data.
In this course, we will take a look at different aspects of research data management along the data life cycle: From data management planning to data publication and preservation. In all those steps, the goal are FAIR data: findable, accessible, interoperable and reusable.
While we focus on research data management, the same topics arise in companies (often called "data governance") and require similar solutions there.
The course aims to enable students to properly manage their own data, but also to advise others on how to do that. |
