Research Article
Understanding Self-Reflection: How People Reflect on Personal Data Through Visual Data Exploration
@INPROCEEDINGS{10.1145/3154862.3154881, author={Eun Kyoung Choe and Bongshin Lee and Haining Zhu and Nathalie Riche and Dominikus Baur}, title={Understanding Self-Reflection: How People Reflect on Personal Data Through Visual Data Exploration}, proceedings={11th EAI International Conference on Pervasive Computing Technologies for Healthcare}, publisher={ACM}, proceedings_a={PERVASIVEHEALTH}, year={2018}, month={1}, keywords={personal informatics visualization self-reflection visualization insights quantified self self-tracking health}, doi={10.1145/3154862.3154881} }- Eun Kyoung Choe
Bongshin Lee
Haining Zhu
Nathalie Riche
Dominikus Baur
Year: 2018
Understanding Self-Reflection: How People Reflect on Personal Data Through Visual Data Exploration
PERVASIVEHEALTH
ACM
DOI: 10.1145/3154862.3154881
Abstract
Rapid advancements in consumer technologies enable people to collect a wide range of personal data. With a proper means for people to ask questions and explore their data, longitudinal data feeds from multiple self-tracking tools pose great opportunities to foster deep self-reflection. However, most self-tracking tools lack support for self-reflection beyond providing simple feedback. Our overarching goal is to support self-trackers in reflecting on their data and gaining rich insights through visual data exploration. As a first step toward the goal, we built a web-based application called Visualized Self, and conducted an in-lab think-aloud study (N = 11) to examine how people reflect on their personal data and what types of insights they gain throughout the reflection. We discuss lessons learned from studying with Visualized Self, and suggest directions for designing visual data exploration tools for fostering self-reflection.
