  This article assesses the experience with i-Log at the European Big Data
Hackathon 2019, a satellite event of the New Techniques and Technologies for
Statistics (NTTS) conference, organised by Eurostat. i-Log is a system that
allows to capture personal big data from smartphones' internal sensors to be
used for time use measurement. It allows the collection of heterogeneous types
of data, enabling new possibilities for sociological urban field studies.
Sensor data such as those related to the location or the movements of the user
can be used to investigate and have insights on the time diaries' answers and
assess their overall quality. The key idea is that the users' answers are used
to train machine-learning algorithms, allowing the system to learn from the
user's habits and to generate new time diaries' answers. In turn, these new
labels can be used to assess the quality of existing ones, or to fill the gaps
when the user does not provide an answer. The aim of this paper is to introduce
the pilot study, the i-Log system and the methodological evidence that arose
during the survey.
