Dataset. In this study, we utilize the RepoRT dataset, an evolving "machine learning ready" repository for retrieving RTs with chromatographic metadata. At the time of access, RepoRT contained 392 different methods, 172,416 total retention times for 94,788 unique molecules represented by SMILES strings. RepoRT is a superset of a variety of commonly used retention time datasets including the METLIN SMRT, Retip, and PredRet datasets, and it contains RTs measured on reversed phase (RP), HILIC, and amide columns. For each method included in the dataset, there is a rich description of the column metadata that includes time-variant gradient profiles, mobile phase additives, intrinsic column parameters, calculated Tanaka and HSMB column parameters, among other descriptors of chromatographic conditions. While RepoRT dataset does perform preliminary filtering of retention times (error thresholds and void volumes), we employed additional filtering steps to maximize the learnability of the dataset and the representation of chromatographic parameters.