With these challenges in mind, quantum-mechanical methods were used to calculate the geometries and descriptors for a wide range of bidentate organophosphorus ligands using a square planar [ligand]PdCl2 complex as the model system (Fig. ). We have previously used a similar strategy with pyridine-oxazoline ligands and found that parameters could be effective in models for reactions that use other transition metals. The computational workflow included a molecular mechanics-based method to generate conformations of the model complex, which were subsequently optimized using DFT. Steric, electronic, and geometric parameters such as those shown in Fig. were collected from the DFT-optimized structures of both the Pd complex as well as the ligand without PdCl2. Of particular importance, parameters were required to reflect quadrant-specific descriptors for ligands containing different symmetry elements. To illustrate this, one may consider the percent buried volume (Vbur) of the northwestern quadrant 30 for a C2v symmetric ligand such as Xantphos (Fig. ). For these symmetric ligands, all four quadrants are symmetry equivalent. However, the optimized ground-state geometries are often significantly distorted out of C2v symmetry and as a result, the quadrant buried volume parameters are not equivalent. This apparent contradiction of symmetry-equivalent quadrants with markedly different parameter values can be understood by considering the ligand's conformational equilibrium-applying the two symmetry operations of the C2v point-group (a C2 rotation and a σh reflection) produces degenerate conformers of Xantphos (Fig. ). As each quadrant can access four different degenerate conformations, we report the minimum, maximum, and average values of the symmetry-equivalent quadrant-specific parameters. Analogous symmetry considerations were applied to ligands of the Cs and C2 point groups (see the SI for further discussion). This parameterization process enabled the effective comparison of disparate ligand backbones. After descriptor library construction, we turned our attention to the visualization of the ligand parameter space (Fig. ). For many virtual molecular libraries, chemical space representations are generated using dimensionality reduction techniques such as principal component analysis (PCA). This results in a graphical depiction of the property space in which the proximity of ligands reflects their similarity. A potential drawback of such dimensionality-reduced maps, especially those encompassing numerous descriptors, is that their axes can be inherently challenging to interpret, as is the case for our bisphosphine descriptor library. Therefore, we set out to develop a chemical space representation that would include more readily interpretable axes akin to a classical Tolman map, while also incorporating multi-dimensional information of modern PCA plots. To accomplish this, parameters were selected from recognizable bins: steric, electronic, and geometric. Examples from each of these categories are depicted in Fig. .