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This paper describes a dataset collected at the end of 2020 as part of the WeNet project, a Horizon 2020 funded project that aims at developing a diversity-aware, machine mediated paradigm for social interactions. The aim of the survey was to measure aspects of diversity based on social practices and related daily behaviours. The data collection was organized in two phases. The first involved a large sample of university students from five universities, located in Denmark, Italy, Mongolia, Paraguay and the United Kingdom. The respondents had to fill a survey aimed at investigating their social practices and specific socio-demographic, cultural and psychological elements. In the second phase, a sub-sample of the respondents participated to a 4 weeks data collection in which they were asked to fill in a self-reported time diary. This was done via a smartphone application, called iLog, which was also collecting data from thirty-four smartphone sensors, twenty-four hours a day. This dataset allows to investigate the diversity and daily routines of university students in a multi-layered perspective, both within and across countries, in a synchronic and diachronic way.