A Comparative Evaluation of Animation & Small Multiples for Trend Visualization on Mobile Phones


Matthew Brehmer, Bongshin Lee, Petra Isenberg, Eun Kyoung Choe


We compare the efficacy of animated and small multiples variants of scatterplots on mobile phones for comparing trends in multivariate datasets. Visualization is increasingly prevalent in mobile applications and mobile-first websites, yet there is little prior visualization research dedicated to small displays. In this paper, we build upon previous experimental research carried out on larger displays that assessed animated and non-animated variants of scatterplots. Incorporating similar experimental stimuli and tasks, we conducted an experiment where 96 crowdworker participants performed nine trend comparison tasks using their mobile phones. We found that those using a small multiples design consistently completed tasks in less time, albeit with slightly less confidence than those using an animated design. The accuracy results were more task-dependent, and we further interpret our results according to the characteristics of the individual tasks, with a specific focus on the trajectories of target and distractor data items in each task. We identify cases that appear to favor either animation or small multiples, providing new questions for further experimental research and implications for visualization design on mobile devices. Lastly, we provide a reflection on our evaluation methodology.


A medium.com article Matt wrote about our research https://medium.com/multiple-views-visualization-research-explained/mobiletrendvis-a948fa65bccd

The scientific publication. Pre-print of our IEEE TVCG article: https://arxiv.org/abs/1907.03919

Code: github.com/microsoft/MobileTrendVis