Furthermore, one needs to transfer input data to the appropriate compute system and prepare them in a way that it can be processed by the employed simulation and analysis tools. Further, to perform correct simulations, one needs to define the right settings and numerical input parameters for the simulations, with at least some minimal understanding of the limitations and assumptions of the employed physical models and algorithms. Manually designing and successfully implementing such a pipeline is not only error-prone, but requires the consultation of a computational expert. If the DFT optimisation is run manually by an experienced computational researcher, the direct link to the experiment will be lost. This is a further disadvantage in addition to the extra time the computational researcher needs to spend on a "routine" simulation.