The eCSNs have been used to visualize the chemical space of 19 large data sets of organic compounds, including natural products, drugs approved for clinical use and other compound libraries, with more than 18 million molecules. As discussed in that paper, this novel representation of the chemical space based on molecular fingerprints is an efficient method to compare the structural relationship among compound libraries. Figure shows a visual representation of the chemical space of the 11 compound libraries using RDKit fingerprints. The network shows that ChemDiv and Asinex (which happen to be the least diverse libraries based on RDKit fingerprints) are at the center of the representation with several connections (similarities) with other databases. In particular, ChemDiv (identified with the number 2 in this network: ID, 2) has the most number of connections, and these connections are closer (visualized by darker linkers between the nodes) with other libraries, such as ApeXBio (ID, 0), SelleckChem (ID, 8), and Targetmol (ID, 9). < Figure here >