Responsible research data management (RDM)

Introduction

Increasingly, researchers are expected to make their research data available, in such a way that it is “as open as possible and as closed as necessary”. Additionally, having a data management plan is required by many stakeholders like funding agencies, ethical review boards, or journals.

But what does this mean, and how can you put this into practice? What are the practical consequences of research data management (RDM) and how do you handle personal/sensitive data and take care of long-term preservation, access, and reuse of your data? These and related questions about RDM are the topic of this workshop.

We will discuss best practices for documenting, organizing, sharing, and archiving your research data, including personal data and working in international collaboration settings. You will practice with writing a README and learn how to write or improve the data management plans for your own research projects.

Effectively managing data can help to optimise research outputs, increase the impact of your research, and support open scientific inquiry. After completing this workshop, PhD candidates will be better equipped to manage their data throughout the entire research data lifecycle, from the stage of project planning to the end.

Workshop information

ECTS: 1.5
Number of sessions: 2
Hours per session: 4 hours (session 1), 3 hours (session 2)

Entry level

Besides having some prior experience with research data (could also be in the Bachelor/Master phase), there are no specific entry requirements for this course. For PhD candidates, we recommend that you follow this course in the first year of their project, if possible. This will help implement the best practices in RDM from the start of your project and to avoid overlap with other RDM trainings that you might follow during your PhD.