The Alexandria database represents an important resource for materials science research, containing more than 5 million density-functional theory calculations for periodic three-, two-, and one-dimensional compounds. This open-access database addresses the critical challenge of data scarcity in materials science, where large, high-quality, and consistent datasets are rare. The Alexandria...
The NOMAD data infrastructure provides access to vast amounts of data that can be used for data analytics and machine learning (ML). Often, however, not all (meta)data are relevant for every task, making it necessary to apply filtering and processing steps to prepare input data for ML. Here, we present MADAS, a Python framework that supports all steps of data analytics and machine learning,...