QCSubmit also facilitates the aggregation of completed calculations across multiple QCFractal instances and datasets into a single local results collection. In line with the dataset creation workflow, results collections can also be processed with many common filtering components such as net charge, element coverage or SMARTS queries, which allows users to construct customized datasets for training or testing of FFs, or even ML models. Datasets can be serialized to JSON and used as a source of provenance. These are lightweight references to the calculations that store only vital information, such as the SMILES ,