Visualization of chemical spaces usually consists of three main steps. In the first step, molecular representations (e.g. SMILES or InChI) are converted into binary or real-value arrays. Each element of the array corresponds to a dimension in the chemical space. In the second step, the high-dimensional chemical space is reduced to 2D or 3D spaces. In the final step, the reduced chemical space is converted into a visual representation. Fingerprints and descriptors are the most widely used molecular encoding methods for the first step. Principal component analysis (PCA) , self-organized maps (SOM) , multidimensional scaling (MDS) , and t-distributed stochastic neighbor embedding (t-SNE) are the commonly used dimensionality reduction methods. Finally, visualizations can take the shape of either 2D or 3D, static or interactive, scatter or grid-like plots. In addition to these, there are alternative chemical space visualization approaches including the minimum spanning-trees , similarity networks , and uniform manifold approximation and projection (UMAP) .