TY - GEN
T1 - Data Every Day
T2 - 2022 CHI Conference on Human Factors in Computing Systems, CHI 2022
AU - Bressa, Nathalie
AU - Vermeulen, Jo
AU - Willett, Wesley
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/4/29
Y1 - 2022/4/29
N2 - We explore the design and utility of situated manual self-tracking visualizations on dedicated displays that integrate data tracking into existing practices and physical environments. Situating self-tracking tools in relevant locations is a promising approach to enable reflection on and awareness of data without needing to rely on sensorized tracking or personal devices. In both a long-term autobiographical design process and a co-design study with six participants, we rapidly prototyped and deployed 30 situated self-tracking applications over a ten month period. Grounded in the experience of designing and living with these trackers, we contribute findings on logging and data entry, the use of situated displays, and the visual design and customization of trackers. Our results demonstrate the potential of customizable dedicated self-tracking visualizations that are situated in relevant physical spaces, and suggest future research opportunities and new potential applications for situated visualizations.
AB - We explore the design and utility of situated manual self-tracking visualizations on dedicated displays that integrate data tracking into existing practices and physical environments. Situating self-tracking tools in relevant locations is a promising approach to enable reflection on and awareness of data without needing to rely on sensorized tracking or personal devices. In both a long-term autobiographical design process and a co-design study with six participants, we rapidly prototyped and deployed 30 situated self-tracking applications over a ten month period. Grounded in the experience of designing and living with these trackers, we contribute findings on logging and data entry, the use of situated displays, and the visual design and customization of trackers. Our results demonstrate the potential of customizable dedicated self-tracking visualizations that are situated in relevant physical spaces, and suggest future research opportunities and new potential applications for situated visualizations.
KW - personal data
KW - self-tracking
KW - situated visualization
UR - https://www.scopus.com/pages/publications/85130572997
U2 - 10.1145/3491102.3517737
DO - 10.1145/3491102.3517737
M3 - Conference contribution
AN - SCOPUS:85130572997
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 30 April 2022 through 5 May 2022
ER -