Chemical Checker [15] signatures were proposed in order to facilitate the conversion of bioactivity data to a format readily amenable to ML methods. The concept of chemical space is continuing to evolve. Its application has been extended to data visualization and to the study of structure-property relationships, lead optimization, data fusion, and data-driven decision making, to name a few applications. However, many different types of descriptors are available to represent different classes of compounds, e.g., natural products, peptides, metallodrugs, drug-like, and lead compounds. The extensive list of possible molecular representations raises a significant question, viz. "what are the most suitable descriptors for my dataset?" In specific cases, the answer combines different kinds of features or types of data such as chemical or topological features, and physical or biological data. However, it is not easy to collect, order, and organize such heterogeneous information. In order to enter an era where chemical and biological spaces are integrated, the development of new methodologies is required for assessing chemical and biological similarity and for handling genes, proteins, omics data, and chemical data in a consistent manner .