In this section, we describe the results of three case studies. These case studies were done by four collaborators (three of them authors), who are experts in the field of chemical RO. We prepared two datasets to be analyzed by the experts who then used CIME4R for (i) understanding and learning from RO campaigns in retrospect (with and without AI-generated data), and (ii) human-AI collaborative decision making. All experts performed their analyses independently of each other. The following sections summarize the more important insights they found and exemplify how CIME4R can be utilized. In the first case study, we asked chemists to use CIME4R to understand a reaction space that has been fully tested experimentally. We chose a subset of a Buchwald-Hartwig reaction dataset performed and reported by Ahneman et. al. . The chosen reaction, as shown in Figure , involves four categories of compounds (three aryl halides substrates, three bases, four ligands, and 22 additives) with a sample of 792 experiments performed. To visualize the experiments in CIME4R, we performed a weighted t-SNE projection using the experiment parameters and their associated descriptors (see Supplementary Material, Additional File 1 for details).