Our self-paced online course allows learners of all levels to learn more about research data management and data literacy at their own chosen pace. Of course, we cordially invite lecturers to use the course in their own teaching.

The course is available in different formats. Upon successful completion of the course on Ilias, learners are issued a certificate of completion. Versions in LiaScript and import files for Ilias and Moodle are designed for reuse. Additionally, the course content was published in a text version.

The self-paced online course is to be continuously improved and updated. Please feel free to send suggestions and feedback to our training team.

On our YouTube Channel, we regularly publish recordings of our training events, in which experts from our diverse partner network – among them data centers, universities and other research institutions – share extensive knowledge from the field.

Topics range from the basics of research data management to modern services and tools for handling biodiversity, ecology, and environmental data throughout the entire data life cycle, and legal aspects.

Our video series "Data Science 4 Ecologists in R" explains basics of reproducible data analysis, starting with tidy data (code & training data sets), followed by linear models (code & training data sets) and polynomial regression analysis. If you would like to follow along, you can find code and training data sets on GitHub.

In cooperation with our partner network, we provide a constantly growing overview of guidelines and training materials in the form of computational notebooks. Computational notebooks are a consise way to publish a combination of text, code and visualisations.

• Introduction to Jupyter (Python & R)
  Get to know the potential of the free and open-source sotware Jupyter. Use the avialable scripts for your own project - for data processing, visualisation or analysis. Created for our Seasonal Schools in collaboration with iDiv and University of Leipzig.

• Exploring Spatial and Biodiversity Data
  This JupyterBook provides students, researchers and lecturers with reproducible code and workflows in Python and JupyterLab to process and analyse spatial and biodiversity data. Basics in Python are useful, but not necessary to follow along. Created in collaboration with IÖR-FDZ.

• Data analysis & visualisation (R)
  This lesson introduces data analysis and visualisation in R with the tidyverse, with a focus on the basics of data visualisation and the "grammar of graphics" with the ggplot2 package. Created for our Seasonal Schools in collaboration with Cédric Scherer.

• Taxonomic name harmonization (R)
  One of the biggest challenges when working with biodiversity data is the the integration of taxonomic data from different sources. Here you learn how to check taxonomic data for typos and synonymes, and how to standardise them with a common taxonomic backbone. Created for our Seasonal Schools in collaboration with PlantHub, an iDiv platform, and the University of Leipzig.

• PANGAEA Data Validation (Python, R)
  With our Jupyter Notebooks, you can check the quality of your data before submitting it to PANGAEA, the digital repository for earth system research and environmental science data.

Some of these computational notebooks are introduced in lecture recordings from our Seasonal Schools.

Our podcast Rechtsdschungel – Recht und Ethik im Umgang mit Biodiversitäts- und Umweltdaten invites listeners to learn about various legal regulations and challenges that can arise when working with biodiversity data and to discover solutions together with us. The podcast will cover general topics on legal aspects of handling research data, such as GDPR, copyright and usage rights, licenses and data sharing, as well as specific topics such as the Environmental Information Act and the Nagoya Protocol (including digital sequence information). In addition, legal issues related to citizen science will also be addressed, as these play an important role especially in the collection of biodiversity data.

In the NFDI4Biodiversity-Zenodo-Community, we provide numerous presentation slides, code, computational notebooks and training data sets on a large range of training topics for free reuse.

The materials are designed for lecturers, students, and researchers in the field of biodiversity, ecology, and environmental studies. From professors looking to expand their teaching materials to students looking for self-study materials, our curated materials cover a wide variety of topics.

You can find a list of all available training resources in our Knowledge Base.