Materials science comprises a multitude of different techniques, be it experimental sample synthesis, preparation, and characterization or theoretical and computational approaches to model these experimental observations, providing predictions of new materials and their properties. In the lab, the same sample is often characterized from different perspectives, applying different experimental probes to it. Likewise, calculations for the same material are performed with various levels of sophistication, often depending on each other. Workflows for sample synthesis, for acquisition, and postprocessing of experimental data, and for managing complex calculations are required to orchestrate these tasks. The huge number of experimental materials laboratories and theoretical materials-science groups, covering the breadth of the field, are working with a large variety of tools, often created in parallel in different sub-fields. In this work, we focus on materials science at the atomistic level. We review the current state-of-the-art workflow definitions in the field of first-principles calculations and provide examples of experimentdriven approaches. We analyze the need for workflows to be interoperable and reusable, and demonstrate the benefits of advanced workflow support within a modern research data management system, using the NOMAD software and repository as a quintessential example.
Speckhard et al. (Thu,) studied this question.