Rheumatic and Musculoskeletal Diseases (RMDs) are very common and can negatively impact patients' quality of life. The current care of patients with RMDs is episodic, based on a few yearly doctor visits, which may not provide an adequate picture of the patient's condition. Researchers have hypothesized that RMDs could be passively monitored using smartphones or sensors, however, there are no datasets to support this development. We introduce the COTIDIANA Dataset: a holistic, multimodal, multidimensional, and open-access resource that gathers data on mobility and physical activity, finger dexterity, and mental health, key dimensions affected by RMDs. We gathered smartphone and self-reported data from 31 patients and 28 age-matched controls, including inertial sensors, keyboard metrics, communication logs, and reference tests/scales. A preliminary analysis showed the potential for extracted metrics to predict RMD diagnosis and condition characteristics. Our dataset shall enable the community to create mobile and wearable-based solutions for patients with RMDs.