Qualified Selves: Co-Creating Meaning Post- Big Data
Qualified Selves: Co-Creating Meaning Post-Big Data addresses the untapped potential of tracking personal data as a medium for generating key insights from patterns of behaviour, physiological responses, productivity, to enable personal reflection and greater self-knowledge.
While personal information collected by services and applications aids companies in identifying likely consumers and generating revenue, there are no corresponding tools for individuals to learn about themselves through their personal data. Qualified Selves seeks to extend personal information management research by lifting data from the UX-constrained applications, to support individualised, goal-oriented collection and management of personal data.
The project has two main objectives: 1) understanding what kinds of self-knowledge would offer significant value to individuals, and how bridging personal data between applications and services might afford personal insights, 2) understanding how people can derive meaning from data types across applications, unbounded by the goal orientations of the individual data-collecting services.
The project is led by principal investigator Professor Chris Speed of the University of Edinburgh. Co-investigators are Bran Knowles, Professor Leon Cruickshank, and Dr Dan Richards, all of Lancaster University. The project is funded by the Engineering and Physical Sciences Research Council (EPSRC).