  We propose a model of the situational context of a person and show how it can
be used to organize and, consequently, reason about massive streams of sensor
data and annotations, as they can be collected from mobile devices, e.g.
smartphones, smartwatches or fitness trackers. The proposed model is validated
on a very large dataset about the everyday life of one hundred and fifty-eight
people over four weeks, twenty-four hours a day.
