Proper research data management (RDM) is becoming an important prerequisite for the successful approval and execution of research projects.

This two-day course will provide you with the essential knowledge and skills to enhance the management of the research data in your PhD project, with a specific focus on storing and organizing your research data.

Day I
On the first course day, RDM experts of the University of Basel will teach you about the basic principles, methods, tools, and legal aspects of RDM. In addition, you will receive practical advice on data documentation and metadata, data publication and reuse, data protection, and useful RDM services.

Day II
On the second course day, you will get an in-depth training on data storage and data organization. In exercises on workflows and tools, you will gain experience to improve the organization of research data in your PhD project. Further, you will have the opportunity to discuss your RDM challenges with RDM service providers and data stewards of the University of Basel.

• You know and understand basic principles, methods and tools for RDM in the health sciences.
• You are able to apply the gained knowledge to plan your RDM and to store, organize, document and publish your own research data.
• You are able to critically assess your own RDM and you are familiar with the most important RDM service providers at the University of Basel.
• You are able to discuss RDM-related topics in a scientific context with other researchers.

Min. 6 and max. 17 participants

Markus Bossert is a coordinator of the Data Stewardship Program and the Research Data Management Network of the University of Basel. He has long-term experience in research data management and works in the Open Science Department at the University Library.

Dr. Stephanie Heinrich is a coordinator of the Data Stewardship Program and the Research Data Management Network of the University of Basel. She works in the Open Science Department at the University Library and likes to pass on her many years of experience in research and her profound knowledge in research data management.

30 hours, of which 15h course attendance, 1 ECTS

Course Assessment (Pass/Fail) criteria

1. Seminar preparation (20%). Participants are expected to familiarize themselves in advance with the topic of research data management, using the provided training materials.
2. Seminar participation (50%). Participants are expected to attend and actively participate in the two course days.
3. Homework assignments & post-processing (30%). Participants are expected to do hands-on exercises on selected RDM topics between and after the course days to train their practical RDM skills.

All course preparations and homework assignments must be completed in the given time in order to pass the course and receive 1 ECTS point. Learning contract required.