The harAGE corpus is a novel dataset for Human Activity Recognition (HAR) collected with a customised app running on a Garmin Vivoactive 3 smartwatch. This dataset contains 17 h 37 m 20 s of data from 30 participants (14 f, 16 m), with a mean age of 40.0 (± 8.3) years old. The available data is split in 3 (train/devel/test) participant-independent and gender-balanced partitions, and contains samples of the 30 participants performing 8 different activities (lying, sitting, standing, washing hands, walking, running, stairs climbing, and cycling). A detailed documentation of this dataset can be found in [1]. If you use the harAGE Corpus in your research work, you are kindly asked to cite [1] and [2] in your publications. [1] A. Mallol-Ragolta, A. Semertzidou, M. Pateraki, and B. Schuller, “harAGE: A Novel Multimodal Smartwatch-based Dataset for Human Activity Recognition,” in Proceedings of the 16th International Conference on Automatic Face and Gesture Recognition, (Jodhpur, India – Virtual Event), IEEE, 2021. [2] B. Schuller, A Batliner, S. Amiriparian, C. Bergler, M. Gerczuk, N. Holz, P. Larrouy-Maestri, S. Bayerl, K. Riedhammer, A. Mallol-Ragolta, M. Pateraki, H. Coppock, I. Kiskin, M. Sinka, S. Roberts, "The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitos," in Proceedings of 30th International Conference on Multimedia, (Lisbon, Portugal), ACM, 2022.