Addressing fundamental questions in the life sciences involves gleaning information from data acquired from wet-lab experiments and simulations. State-of-the-art analyses ensuring the highest standards are only possible if each step—from data acquisition and processing to any form of modification—is documented properly. Promoting effective data governance and ensuring that all data and metadata, as well as the source code of publicly available software, is documented is key for long-term reproducibility; in short, it forms the basis of excellence in research and scientific integrity. Furthermore, proper data management allows the reuse and re-analysis of data for different purposes, and helps investigators be transparent with respect to the scientific community. These and other considerations have led to the proposition of FAIR data principles that, when properly adopted, allows scientists to find, access, interoperate and reuse research data. Scientists from various fields are currently improving existing workflows to meet these standards. The development of sustainable solutions for research data management (RDM) is strongly supported by the national research data initiative (Nationale Forschungsdateninfrastruktur, NFDI) funded by the DFG.