Winter School on Data Management in Ecology and Environmental Science – December 5-9, 2022

The Winter School will provide state-of-the-art skills and knowledge in handling scientific data across the data life cycle and is a cooperation between the Ecological Society (GfÖ) and the National Research Data Infrastructure (NFDI4Biodiversity). Various experts from our partner network (universities, data centers and research institutions) are invited as speakers and will share their knowledge with the participants. In a combination of direct knowledge transfer and practical lessons, participants will be introduced to fundamentals and cutting edge tools in the field and how to use them for their future careers. The winter school provides a unique opportunity to get introduced to advanced knowledge in research data management including the handling of data across technical borders such as combining different programming languages and/or software tools in a very short amount of time.

*** Please note: Due to great interest, the Winter School is already fully booked. We are working on offering another course as soon as possible. ***

Basic information

When? December 5-9, 2022 

Where? Fully virtual

Credit? None

Charges? None

Language? English


  • Prof. Dr. Carsten Dormann (University of Freiburg)
  • Prof. Dr. Birgit Gemeinholzer (University of Kassel)
  • Dr. Matthias Grenié (iDiv - German Centre for Integrative Biodiversity Research)
  • Prof. Dr. Dennis-Kenji Kipker (University Bremen)
  • Dr. Ivaylo Kostadinov (German Federation for Biological Data)
  • Jimena Linares (German Federation for Biological Data)
  • Priv.-Doz. Dr. Wolfgang Müller (HITS - Heidelberg Institute for Theoretical Studies)
  • Dr. Michael Oellermann (MARUM – Cen­ter for Mar­ine En­vir­on­mental Sci­ences / PANGAEA)
  • Dr. Hanieh Saeedi (Senckenberg - Leibniz Institution for Biodiversity and Earth System Research)
  • Sophie Wolf (University of Leipzig)

Organizational Team

  • Marlen Fischer (University Marburg)
  • Juliane Röder (University Marburg)
  • Dr. Daniel Tschink (German Federation for Biological Data)

Please feel free to contact us ( if you have specific inquiries.

Target group

PhD students and Early-Career Researcher with background and interest in ecology, biodiversity and environmental sciences.

Learning Outcomes

The participants will gain advanced knowledge on data management across the data life cycle. The lecturer will teach theoretical and practical aspects of Research Data Management (RDM) focused on challenges and characteristics specifically important in handling ecological data (e.g. handling of spatial data). In the practical lessons, participants will be introduced to Jupyter Notebook as a powerful RDM and development environment for notebooks, code and data. Jupyter is a free software tool which allows you to combine data management and publication features while integrating different programming languages. Thus, it is a perfect tool for interdisciplinary working environments. Beside the general introduction to Jupyter, the lecturer will teach how to combine software tools e.g. Jupyter, R, Python, Excel. Lectures will be given by experts in the respective field. Participants will obtain knowledge in the following matters:

  • How to create a data management plan
  • How to use Jupyter in combination with R, Python as working environment
  • How to standardize data
  • Legal aspects in handling data
  • How to handle spatial data
  • How to extract data from open-access databases
  • How to assure data quality
  • How to integrate & harmonize data
  • How to publish data


*** REGISTRATION CLOSED: We are pleased with the great interest in participating in the Winter School. Unfortunately, the available places are already fully booked. Should this change, we will inform you here. We will try to offer the course again in the near future. ***

Learning Modules

Each day of the Winter School starts with a 30 minutes "Warm-Up" as a networking opportunity followed by two lectures and a practical lesson. Each lecture focuses on a specific topic and will gain insight into the fundamentals and/or respective tools.

Tentative Schedule

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