Tracking social rhythms of the heart: from dataism to art
Mustonen, Veera; Pantzar, Mika (2013)
The Donner Institute, Åbo Akademi
Veera Mustonen (MA) is a cognitive scientist and senior researcher at the National Consumer Research Centre in Helsinki, Finland. She is a doctoral student in industrial engineering and management at Aalto University. Her research focuses on the emerging digital Health 2.0 field, behavioural change and the human–machine relationship. Prior to her current academic pursuits, she worked for 13 years in the industry developing human technologies such as smartphones (for Nokia) and eLearning systems (for Sanoma WSOY). Mika Pantzar is a research professor at the National Consumer Research Centre in Helsinki, Finland. He received his doctorate in the field of management and organizations at the Helsinki School of Economics and Business Administration. Among his current research interests are the economics of sport, health and wellbeing, and, relatedly, the big data and quantified self movement. He has published articles widely within consumer research, design and technology studies, the rhetoric of economic policy, food and future studies and systems research. Recently he co-authored a book with Elizabeth Shove and Matt Watson entitled Everyday Life: The Dynamics of Social Practice (Sage 2012).
The authors conducted a curiosity-driven study to explore what a vast body of self-tracking data could reveal about the rhythms of everyday life. The authors instructed thirty-six research participants to engage in self-tracking for a week. They measured their physiological stress and recovery 24/7 for this period. In addition to that the participants recorded their subjective experiences of stress and recovery. Using different methods of analysis and interviews, the authors were able to form data sets demonstrating both individual behaviour and interpretations of the data and the collective rhythms of all the participants. Their analysis contrasted the aggregate-level 'big data' of all the participants and the personal-level 'small data'. People’s subjective evaluations of their stress and recovery systematically differed from the physiological measurements. The big data revealed behavioural patterns and causalities that were not recognized at the individual level. The small data, on the other hand, offered rich material for personal interpretations and reflections of the individuals' own lives. To communicate both levels of the data the science project resorted to artistic expressions.