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Introduction to Research Data Management

Implementing good research data management (RDM) practices requires effort and time, but brings significant benefits, such as improved visibility and impact of your research, increased data quality and integrity, compliance with good research practice and data management policies. Understanding the basic principles and tools will help you integrate RDM more efficiently into your daily research workflows.

About

These are the recommended guidelines for research data management at the UFZ. The Structure and content of these guidelines are fundamentally based on the FDMentor project's train-the-trainer concept on research data management. Basically, most of the credit goes to the guys behind FDMentor1. At UFZ, we adopted the presented structure, customized it to the needs of the communities at UFZ and garnished it with the specifics of environmental research.

Content

This course provides basic knowledge for our complementary hands-on courses on RDM tools. Furthermore, the course provides important basics for a better understanding of the standard operating procedure (SOP), which exist for different application areas within research data management at UFZ.

  1. Biernacka, Katarzyna, Bierwirth, Maik, Buchholz, Petra, Dolzycka, Dominika, Helbig, Kerstin, Neumann, Janna, Odebrecht, Carolin, Wiljes, Cord, and Wuttke, Ulrike. (2020). Train-the-Trainer Concept on Research Data Management (3.0). Computer software. doi.org/10.5281/zenodo.4071471. Zenodo. ↩