Visualization of Quantified Self with movement and transport data

Sammanfattning: Transport systems account for a large part of the worlds CO2 emissions. In order to reach goals, set to lower emissions, we need to travel less by car and increase the use of sustainable means of transportation. Through the use of self-tracking devices and by visualizing the data collected, individuals can learn about, and discover, habits, patterns and practices amongst themselves. In this thesis, the question of how much individuals know about their own CO2 emissions created from the modes of transportation they use on an everyday basis, is explored. The paper examines how a visualization of personal movement and transport data affects individuals' understanding of their own CO2 emission as well as their motivation towards using more sustainable modes of transportation. A two-week user-study was conducted with 15 participants. The participants tracked their movements and transports using a mobile application on a smart phone, and their data was presented in a web-application. Prior and post to the user-study, a self-evaluation questionnaire based on the COM-B model was handed out. Results showed that participants' understanding increased regarding putting their emission amounts in relation to what is low and what is high between transportation modes. An increased awareness of personal transportation patterns and what the environmental impact the choice of transport mode has, was indicated. Further, participants' motivation towards using more sustainable modes of transportation seems to be dependent on realizing if they have low or high emissions but also if there exist available alternative transport options to switch to.