Many personal informatics systems allow people to collect and manage personal data and reflect more deeply about themselves. However, these tools rarely offer ways to customize how the data is visualized. In this work, we investigate the question of how to enable people to determine the representation of their data. We analyzed the Dear Data project to gain insights into the design elements of personal visualizations. We developed DataSelfie, a novel system that allows individuals to gather personal data and design custom visuals to represent the collected data. We conducted a user study to evaluate the usability of the system as well as its potential for individual and collaborative sensemaking of the data.
Abstract
Many personal informatics systems allow people to collect and manage personal data and reflect more deeply about themselves. However, these tools rarely offer ways to customize how the data is visualized. In this work, we investigate the question of how to enable people to determine the representation of their data. We analyzed the Dear Data project to gain insights into the design elements of personal visualizations. We developed DataSelfie, a novel system that allows individuals to gather personal data and design custom visuals to represent the collected data. We conducted a user study to evaluate the usability of the system as well as its potential for individual and collaborative sensemaking of the data.
Available Versions
Citation Information
Nam Wook Kim, Hyejin Im, Nathalie Henry Riche, Alicia Wang, Krzysztof Gajos, and Hanspeter Pfister. Dataselfie: Empowering people to design personalized visuals to represent their data. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, CHI '19, pages 79:1-79:12, New York, NY, USA, 2019. ACM.
BibTeX