Online courses

New learning unit available on Moodle: Research Data Management for Biodiversity Data

A new English-language learning unit is available in OpenMoodle: Based on the general introduction to research data management, the NFDI4biodiversity has created the learning unit Research Data Management For Biodiversity Data.
This course provides basic knowledge on research data management. Prerequisites: No previous knowledge necessary. Chapters build on each other, but can also be worked on individually. Target group: Master's and doctoral students as well as researchers in biology and environmental sciences who are looking for an introduction to research data management. Learning objectives: Understand the content and purpose of research data management and be able to apply it in biology. Learning objectives are stated at the beginning of each chapter.

Current events

Please note that our online courses are currently only available in German.

You can find our live formats on the university's event pages.

Current events: Zu Campus Events

Recently, videos on the topic of research data were collected and sent out on a weekly basis. Click here for the list of videos.

Zur Video-Kampagne

HeFDI Data School 2024/25

The HeFDI Data School offers cross-location and interdisciplinary courses on research data management. It is aimed equally at doctoral students and academic staff at Hessian universities and beyond.

The basic modules provide (initial) orientation in research data management (RDM). They focus on basic concepts, standard methods and best practices. The additional modules offer an in-depth insight into selected sub-areas.

Introduction to research data management - an online introduction to Moodle

The interactive Moodle course was jointly developed in HeFDI - Hessian Research Data Infrastructures and answers questions such as "What is research data management? Why is it important? Research data management and third-party funding applications - yes, but how?" Current topics relating to RDM are illustrated using videos, quizzes and numerous examples of good practice. The chapters build on each other thematically, but can also be used and worked on individually.


The target group includes:

  • Researchers (professors, research assistants, doctoral candidates) who produce, analyze and later share data themselves, and possibly also reuse other data

  • Teachers, also for use in their courses

  • Students who want to familiarize themselves with FDM (even before their Bachelor's or Master's thesis)

Contents of the self-study unit:

  1. Introduction to research data management
  2. The life cycle of research data
  3. The data management plan
  4. Metadata and metadata standards
  5. FAIR principles and CARE principles
  6. Data quality
  7. Data organization
  8. Data storage and archiving
  9. Legal aspects of research data management