The experimental and theoretical projects of the SFB/TR103 generate large data sets on processing, on microstructure and on the thermodynamic, kinetic and mechanical properties of single-crystal superalloys. The key to understanding and optimizing the properties of single crystal superalloys is the intelligent and scale-bridging correlation of the data that is highly heterogeneous in content and character. This leads to requirements regarding the storage and interlinking of research data and the corresponding research data management (RDM) at the level of individual projects and at the level of the whole SFB/TR103 consortium. Main elements of data handling at the consortium level are birth-certificates of the experimental samples, a central general-purpose file-server, an RDM panel for establishing a common basis of data management and a cross-sectional group 'Material informatics and machine learning' for coordinating the correlation and utilization of the data. At the project level the solutions are more tailored towards special-purpose application and include commercial and specially developed databases as well as protocols for that standardize the workflows of data exchange. A central aim that is pursued in coordination with national and international RDM activities is to make the research data of the SFB/TR103 available as FAIR data for later scientific usage. The particular challenge is the structured storage of disperse data that range from simulation data at different length and time scales to image information from electron-microscopes and atom-probe tomography to mechanical and micromechanical data from nanoindentation, creep and fatigue experiments.