Data is playing an increasingly important role in all research areas. Anyone who has worked with data knows about the many possibilities and opportunities, but also about the challenges. It is easy to lose track: What kind of data am I dealing with? How can I or perhaps how do I have to file it? Which steps do I have to document? How do I find suitable solutions for my work that make my life easier and not more difficult? Etc.

In this workshop, participants will gain knowledge about basic data management issues and learn tips and tricks for handling data. The following topics will be covered:

-        Handling data along the research process

-        Different types and qualities of data

-        Data documentation and -organizations (also in working groups)

-        Handling meta data

-        Making data available for further research

Using intelligible examples from the social sciences, the use and documentation of data is illustrated. In practical exercise phases, participants work on their own projects from different disciplines. In this way they become familiar with a variety of data, each with its own specific challenges.

Learning Objectives: You

-        are aware of the scientific necessity and the practical benefit of research data management (RDM) for (your own) research.

-        know the stages of the research data cycle, central basic terms as well as information portals/documents of RDM (also those of KIT).

-        are able to locate your project in the RDM cycle and to name the challenges associated with it.

-        know the challenges of publication bias and approaches to counteract it.

-        can create a preregistration in broad terms and know the benefits in relation to RDM.

-        are aware of the diversity of data (qualitative & quantitative) and can reflect on differences in relation to the challenges of RDM.

-        are able to reflect on your data organization, identify weaknesses and look for solutions.

Work Expenditure:

2 ECTS: Active participation in the seminar, completion of 2 Data Challenges, preparation of a Reflection Essay (approx. 3 pages).

Anmeldung unter studium@hoc.kit.edu