TY - JOUR
T1 - Visualization in Motion: A Research Agenda and Two Evaluations
AU - Yao, Lijie
AU - Bezerianos, Anastasia
AU - Vuillemot, Romain
AU - Isenberg, Petra
PY - 2022/6/21
Y1 - 2022/6/21
N2 - We contribute a research agenda for visualization in motion and two experiments to understand how well viewers can read data from moving visualizations. We define visualizations in motion as visual data representations that are used in contexts that exhibit relative motion between a viewer and an entire visualization. Sports analytics, video games, wearable devices, or data physicalizations are example contexts that involve different types of relative motion between a viewer and a visualization. To analyze the opportunities and challenges for designing visualization in motion , we show example scenarios and outline a first research agenda. Motivated primarily by the prevalence of and opportunities for visualizations in sports and video games we started to investigate a small aspect of our research agenda: the impact of two important characteristics of motion—speed and trajectory on a stationary viewer's ability to read data from moving donut and bar charts. We found that increasing speed and trajectory complexity did negatively affect the accuracy of reading values from the charts and that bar charts were more negatively impacted. In practice, however, this impact was small: both charts were still read fairly accurately.
AB - We contribute a research agenda for visualization in motion and two experiments to understand how well viewers can read data from moving visualizations. We define visualizations in motion as visual data representations that are used in contexts that exhibit relative motion between a viewer and an entire visualization. Sports analytics, video games, wearable devices, or data physicalizations are example contexts that involve different types of relative motion between a viewer and a visualization. To analyze the opportunities and challenges for designing visualization in motion , we show example scenarios and outline a first research agenda. Motivated primarily by the prevalence of and opportunities for visualizations in sports and video games we started to investigate a small aspect of our research agenda: the impact of two important characteristics of motion—speed and trajectory on a stationary viewer's ability to read data from moving donut and bar charts. We found that increasing speed and trajectory complexity did negatively affect the accuracy of reading values from the charts and that bar charts were more negatively impacted. In practice, however, this impact was small: both charts were still read fairly accurately.
KW - Visualization in motion
KW - Visulaization perception
KW - Research agenda
KW - Crowdsourcing Experiments
KW - Visualization design
UR - https://www.youtube.com/watch?v=sIzRfNIsRV4
UR - https://www.replicabilitystamp.org/index.html#https-gitlab-inria-fr-lyao-visinmotion
UR - https://osf.io/km3s2/
UR - https://www.webofscience.com/wos/woscc/full-record/WOS:000849261100017
UR - https://gitlab.inria.fr/lyao/visinmotion
U2 - 10.1109/TVCG.2022.3184993
DO - 10.1109/TVCG.2022.3184993
M3 - Article
C2 - 35727779
SN - 1077-2626
VL - 28
SP - 3546
EP - 3562
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
IS - 10
M1 - 10.1109/TVCG.2022.3184993
ER -