This research is concerned with the factors that affect the way ordinary people adopt or engage with lifelogging technologies. By ordinary people I mean those who don’t consider themselves to be lifeloggers or members of the Quantified Self movement. Athletes (professional or amateur) or people with particular health issues will often measure aspects of their life to try to improve performance or a particular condition. In this work I’m trying to find out how the automatic collection of data about your life and environment can help you learn things about yourself that you didn’t know that you didn’t know.
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. The so-called Quantified Self movement is mainly concerned with the technologies for collecting and analyzing data within an individual, usually for self-improvement or understanding.
In this research I will be examining and evaluating appropriate devices for lifelogging 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 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 these technologies may be utilized to help individuals achieve their person improvement goals.