A central interest of Caden is the so-called provenance tracking of samples and data. The central requirement is to store data entities (i.e., both data and metadata) and to store parameters of activities (e.g., temperatures, pressures, simulation parameters) in a structured and traceable manner. In addition, entity links must be created to describe a graph topology. The graph can be very complex and non-linear (i.e., contain branches and bifurcations) with a large number of process steps. Another challenge for Caden is the cooperation between different institutions. It is quite common for institutions to have their own individual repositories and metadata schemes, often with little overlap to those of other institutions. Consolidation of process steps (i.e. the fragments of the workflow graphs) across institutional boundaries is often difficult, and as of now there is no way to automate this step (e.g. via machine-processable link). One way to solve this issue is the use of a unified research data infrastructure, such as Kadi4Mat or eLabFTW.

In IMD-2, the two electronic laboratory notebooks (ELN) eLabFTW and Kadi4Mat are to be introduced as part of a structured research data management. In order for these two ELNs to be used effectively by the staff, and in order to find the necessary acceptance for their use, users must be able to recognize a clear advantage and a reduction in workload compared to the paper lab books used up to now. This can be achieved if processes are simplified through the use of templates and through automated data acquisition from connected devices via interfaces (API). Therefore, templates and API's for the many different devices in IMD-2 will be written or programmed in this project.

The “AutoMat” innovation pool project aims to implement the methods of accelerated material development for research into new energy materials and thus integrate the use of advanced technologies such as machine learning, artificial intelligence in general and automation in experimental and simulative approaches. Specifically in this project, a material acceleration platform is to be set up and new materials for batteries are to be found and known materials optimized. New data will be generated and recorded according to the FAIR principles, including through the use of electronic laboratory notebooks and modern research data management methods. Adapted ontologies and knowledge graphs will be developed to enable structured data exchange with other groups and their systems.