Analysing personal datasets has traditionally been limited to `Quantified Selfers' who commit significant effort into manually recording and analysing their data. However, the pool of Casual Users (CUs) who \textit{can} engage with their personal data is increasing due to the prevalence of companies passively collecting user interaction data. In this paper, we execute an online survey exploring what kinds of information users seek about their music listening behaviour. We compare the information needs of CUs to identified Self-Trackers, using music listening as a lens to develop an information space. The paper culminates in a provocation to broaden the audience of personal informatics by updating existing models of interaction to account for casual users, passive data, and episodic reflection.
ACM CHI Conference on Human Factors in Computing Systems