This project will study the digital daily rhythms of individuals and populations with the help of a wide variety of data sets. These range from anonymized data on mobile telephone calls of millions of individuals to detailed behavioural records from apps installed on smartphones of volunteers. The initial focus will be on individuals and better understanding what drives their daily rhythms (communication and online activity at different times of day), from chronotypes related to sleep and wakefulness to different social contexts being emphasized at different times. The studies will then be extended to the population level, leveraging Big Data to study e.g. the different rhythms of life in the countryside versus cities, and the dependence of rhythms of sleep on age. Finally, applications in personalized and digital health will be considered, e.g. algorithms that detect sudden disruptions in daily rhythms may be useful in clinical applications for monitoring mental health patients.