This is the raw data from the empirical investigation of the paper “Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation”. This work aim of this work is to investigate the state of dataset documentation practices, measuring the completeness of the documentation of several popular datasets in ML/AI repositories. We created a dataset documentation schema-the Documentation Test Sheet (DTS)-that identifies the information that should always be attached to a dataset (to ensure proper dataset choice and informed use), according to relevant studies in the literature. We verified 100 popular datasets from four different repositories with the DTS to investigate which information were present.