Certificate Course (Course language: German)

As a third pillar in the professionalization of training in research data management, we offer a certification. Doing so, we developed the module “Data Curation and Management of Sensitive Data in Research Data Centers (RDCs), which was successfully integrated into the RDM Certificate Course at TH Köln in 2024.

The learning agenda of the module is based on the requirements outlined by RDCs. This means that completing this certificate course with our elective module prepares participants very well for working in an RDC.

RDCs differ from other data repositories and play a significant role in handling sensitive data in the social sciences that are not publicly accessible due to legal or ethical reasons. The module provides both fundamental and advanced knowledge about working in RDCs, with a focus on their organizational structure.

Another part of the course is dedicated to the specific competencies and activities involved in the data curation process at the RDC. This competency framework covers organizational tasks and challenges associated with each step of the data curation lifecycle, such as data reception, data acquisition, access, and reuse etc.

A key part of the module is dedicated to the topic of data acquisition in RDCs. Topics include collection policies, data preparation (e.g., anonymization, documentation), archiving, and long-term data availability. Legal frameworks for accepting sensitive data, the ingestion process, as well as data access, usage agreements, and access control are also discussed. Another key focus is on promoting data reuse and investigating usage frequency and purposes.

By the end of the module, participants will be able to explain the specific characteristics of RDCs compared to other repositories, describe the data ingestion process up to the point of data availability, and explain the legal and documentation requirements.

Instructors in the year group 2024/2025:

Alexia Meyermann

DIPF | Leibniz Institute for Research and Information in Education

Dr. Pascal Siegers

GESIS – Leibniz Institut for Social Sciences, Research Data Center ALLBUS