This article presents the DeepSense 6G data-set, which is a large-scale dataset based on real-world measurements of co-existing multi-modal sensing and communication data. The Deep-Sense 6G dataset is built to advance deep learning research in a wide range of applications in the intersection of multi-modal sensing, communication, and positioning. This article provides a detailed overview of the DeepSense dataset structure, adopted testbeds, data collection and processing methodology, deployment scenarios, and example applications, with the objective of facilitating the adoption and reproducibility of multi-modal sensing and communication datasets.