The first service is a computational workflow service. It should help the user go through the process from problem formulation to result generation. For example: prepare the structure, run DFT calculation, save parameters, get source files, perform analysis, prepare dataset.
The second service is FAIR data publication. It is needed to ensure that the results do not remain in local folders. The user receives assistance with preparing the dataset structure, README, metadata, license, DOI, description of methods and connection to the publication.
The third service is reproducibility of the study. It ensures the preservation of input files, program versions, parameters, scripts/notebooks, execution environment and sequence of actions. This is especially important for DFT, MD and MLIP, where a small change in parameters can significantly affect the result.
The fourth service is preparation of use cases. The laboratory can receive assistance in designing its example as a demonstrator: a brief description of the problem, workflow, data, result, publication, scalability, potential European partner.
The fifth service is training and consultations. These are short practical formats: “how to prepare a dataset”, “how to write a README”, “how to get a DOI”, “how to run a Jupyter workflow”, “how to prepare a DMP”, “how to describe an MLIP dataset”.
