@MASTERSTHESIS\{IMM2012-06396,
    author       = "B. S. S{\o}rensen",
    title        = "Personal Visualisation of Spatiotemporal and Social Data",
    year         = "2012",
    school       = "Technical University of Denmark, {DTU} Informatics, {E-}mail: reception@imm.dtu.dk",
    address      = "Asmussens Alle, Building 305, {DK-}2800 Kgs. Lyngby, Denmark",
    type         = "",
    note         = "{DTU} supervisors: Jakob Eg Larsen, jel@imm.dtu.dk, Michael Kai Petersen and Sune Lehmann J{\o}rgensen, {DTU} Informatics",
    url          = "http://www.imm.dtu.dk/English.aspx",
    abstract     = "This thesis is a case study in the analysis, design and implementation of a personal informatics system that enable users to gain self-knowledge and self-reflection. The system, Sensible You, is based on data collected in the Sensible {DTU} project. The Sensible {DTU} project collect data using mobile phones from students and staff participating in a trial.
Privacy issues was analysed and discussed as the data collected and visualised could be regarded as very personal.
Using location and device proximity to infer nearby people, the user is presented with personal visualisations of their data. One visualisation present the user with a map, where they are able to explore how their location changes during the day. Furthermore they are able to playback the data. While analysing the location data it was found that clustering was required. Both
a {K-}Means and a {DBSCAN} algorithm was implemented and evaluated for this task. This resulted in the release of an open source JavaScript clustering library. To visualise the infered social connections, different visualisation options was analysed and evaluated. The result is a chord graph, showing how much time users spent with each other.
The design and implementation of the visualisations was based on theories by Bertin and Tufte, as well as other related work. An evaluation consisting of qualitative user feedback and performance tests was conducted. While the user feedback was limited, it showed good results and participants was positive towards the system and project as a whole.
Perspectives for further work include basic improvements to the project, but also the usage of spatio temporal analysis in a personal informatics context. Furthermore we argue that the privacy issues could be solved by decentralising some of the personal informatics systems."
}