While the primary datasets attempt to capture a wide variety of atomic environments by including a mix of 'typical compound classes', this is mostly based on subjective judgement, and no quantitative measure of 'diversity' was actively considered during its construction. As such, following the initial pass of data generation, a more detailed analysis of the atomic environments is conducted. Rather than characterizing the atomic make-up of the crystal structures only by element, each element is further distinguished by more descriptors, including the atom's coordination number, valency, and immediate bonded neighbours. Because these descriptors are conveniently described by SMARTS notation (Table ), this facilitates use of the CCDC's Python API for analysis of the existing datasets and during the subsequent candidate structure search.