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Research Overview

This research is concerned with the ways in which Personal Informatics (PI) technologies can be used to influence individuals’ behaviour. In particular it explores the technologies available, the factors which influence their adoption and continued use, and how various data can be compared both within an individual and across a group to help a person achieve his or her goals.

PI is a subset of the much older field of lifelogging, a practice that is as old as human beings. From cave paintings to written diaries to family photo albums to blogs, facebook, and flickr people have been manually recording what has been happening in their lives in some kind of durable media. The difference that 21st century technologies have brought is the ability of ordinary people to record automatically and relatively effortlessly a wider range of data about one’s life with a precision and resolution previously only available to elite athletes, scientists and medical staff. These technologies have also provided the ability to store results in a medium that is easily shared, processed, and correlated with other data about the external environment giving people the ability to compare themselves with previous measurements over time or with the current performance of a wider population. While PI is mainly concerned with the technologies for collecting and analyzing data within an individual, PI technologies may also be used to collect data about a group. By utilizing the so-called nudge effect, some people may be guided to modify their behaviour because their performance is regularly compared with that of a group they identify with and they become personally motivated either achieve or exceed the group norm, such as losing weight, using less electricity, or having greener shopping habits. Others may be less motivated by their changing ranking in a group and more so with achieving a personal goal and thus their relative change in performance over time is the key.

In this research I will be examining and evaluating appropriate devices for PI across a range of data types. For each device or system I will be looking at factors such as the level of automation and intrusiveness, the quality of the data, and its ability to share data with other PI systems. I will be looking at some of the common goals individuals have and I will explore which devices and methods of influence (personal comparison, group comparison, or combinations) are best suited to helping a person achieve his or her goal. By determining which methods of data collection, analysis, and comparison are best suited to an individual I hope to provide a measurable improvement in how PI technologies may be utilized to help individuals achieve their person improvement goals.