When doing calculations in material science, a large amount of data needs to be stored in a neat and organized way. This is crucial for ensuring accessibility of the data and usability for future analysis. In addition, some calculations on software like VASP (Vienna Ab initio Simulation Package) or LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) need eventually to be restarted multiple times to achieve convergence or equilibrium criteria. These criteria are essential to validate the results, ensuring they are accurate and reliable.

The process of producing all of this data is certainly labor-intensive, time-consuming, and dependent on many human interventions. However, it can be significantly streamlined using well-written and structured workflows. The general idea of a workflow is to automate and regularize the data generation and analysis process. By doing this, the process becomes easier to manage and more reproducible, with the possibility of tracking the whole process of calculation for checking purposes, allowing for consistent results across different experiments and simulations.

Well-designed workflows not only save time but also reduce the risk of human error, thereby increasing the reliability of the data produced. Here are some of the developments made on the platform in this direction. These advancements aim to enhance the efficiency and reproducibility of material science calculations, ultimately contributing to more robust and reliable scientific findings.