Collection, Processing, and Sharing of a Dataset for the Selective Hydrogenation of Benzene to Cyclohexene

• • The dataset compiles experimental data from 10 literature sources, standardizing catalyst composition, reaction conditions, and outcomes (conversion, selectivity, yield) to enable direct comparative analysis and machine learning modeling. • • Data are provided in Excel (.xlsx) format, accessible via GitHub (https://github.com/ttoono-takaki/Code-and-dataset.git) and ScienceDB (DOI: 10.57760/sciencedb.27385), ensuring reproducibility and reuse. • • The dataset supports statistical analysis and visualization (Figure 1) to identify key influencing factors and correlations, facilitating data-driven experimental design and catalyst screening. • • Quality control procedures address biases from inter-laboratory differences in apparatus and analysis, enhancing data reliability for subsequent modeling and industrial scale-up considerations.