Enabling self-reflection with LifelogExplorer: Generating simple views from complex data

Nowadays, people are overwhelmed with multiple tasks and responsibilities, resulting in increasing stress level. At the same time, it becomes harder to find time for self-reflection and diagnostics of problems that can be source of stress. In this paper, we propose a tool that supports a person in self-reflection by providing views on life events in their relation to person's well-being in a concise and intuitive form. The tool, called LifelogExplorer, takes sensor data (like skin conductance and accelerometer measurements) and data obtained from digital sources (like personal calendars) as input and generates views on this data which are comprehensible and meaningful for the user due to filtering and aggregation options which help to cope with the data explosion. We evaluate our approach on the data collected from two case studies focused on addressing stress at work: 1) with academic staff of a university, and 2) with teachers from a vocational school.