Seasonal School on Data Management in Biodiversity and Environmental Science

Seasonal School on Data Management in Ecology and Environmental Science
Jointly organized by NFDI4Biodiversity, HeFDI, and iDiv – October 06 - 10, 2025

This online Seasonal School is a five-day training designed for early-career researchers who work with biodiversity and environmental data. It focuses on equipping participants with fundamental and domain-specific skills in research data management (RDM), covering important aspects of the data journey: from collection and harmonization to analysis and publication.

Building on the success of previous editions, the 2025 Seasonal School will guide participants through practical tasks using shared data sets, open-source tools, and real-life examples. Morning lectures introduce key topics such as FAIR principles, data repositories, taxonomic harmonization, legal frameworks, and reproducible workflows. Afternoon hands-on sessions provide experience with tools like GitHub, Jupyter, R, OpenRefine, digital fieldwork apps, and more.

Highlights

• Gain practical skills in R, Python, Git, and Jupyter Notebooks
• Learn how to write DMPs using the GFBio tool
• Collect biodiversity data with digital fieldwork apps
• Harmonize taxonomic data and annotate datasets using OpenRefine and RightField
• Explore publication workflows via Zenodo, PANGAEA, and GBIF
• Work in an interactive online setting with expert instructors and peer feedback

Practical Notes

• The Seasonal School is free of charge.
• Sessions will be conducted in English.
• To ensure meaningful interaction, the course is limited to 20 participants.
• Only complete registrations will be considered.
• The application requires an online form and a letter of motivation.
• Guest users (non-Uni Kassel accounts) need register and verify their email address within 24 hours of registration.
• Registration is open from June 30 to August 31, 2025.
• Participants will be notified about admission within one week after the application deadline. (Priority will be given to PhD students at Hessian NFDI4Biodiversity partners (University of Kassel, University of Gießen, University of Marburg) and to members of the iDiv graduate program (yDiv), but participants from all institutions are welcome to apply.)

Further, participants need at least some basic programming experience in R (Python is optional). We provide a list of recommended training materials to meet the required level of data handling skills necessary to follow this course here.

If you are admitted and can no longer attend, please let us know as soon as possible. We usually have a long waiting list, and your spot can be passed on to another qualified applicant.

We look forward to your application!

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PS.: If you are specialized in working with object data from natural science collections, the winter school of the Winoda Knowledge Lab in November 2025 might be of interest to you. You can find more information here: https://winoda.de/events/