4 research outputs found
Evaluating the Effect of Timeline Shape on Visualization Task Performance
Timelines are commonly represented on a horizontal line, which is not
necessarily the most effective way to visualize temporal event sequences.
However, few experiments have evaluated how timeline shape influences task
performance. We present the design and results of a controlled experiment run
on Amazon Mechanical Turk (n=192) in which we evaluate how timeline shape
affects task completion time, correctness, and user preference. We tested 12
combinations of 4 shapes -- horizontal line, vertical line, circle, and spiral
-- and 3 data types -- recurrent, non-recurrent, and mixed event sequences. We
found good evidence that timeline shape meaningfully affects user task
completion time but not correctness and that users have a strong shape
preference. Building on our results, we present design guidelines for creating
effective timeline visualizations based on user task and data types. A free
copy of this paper, the evaluation stimuli and data, and code are available at
https://osf.io/qr5yu/Comment: 12 pages, 5 figure
A Comparative Evaluation of Animation and Small Multiples for Trend Visualization on Mobile Phones
International audienceWe 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