1 research outputs found
Toward A Deep Understanding of What Makes a Scientific Visualization Memorable
We report results from a preliminary study exploring the memorability of
spatial scientific visualizations, the goal of which is to understand the
visual features that contribute to memorability. The evaluation metrics include
three objective measures (entropy, feature congestion, the number of edges),
four subjective ratings (clutter, the number of distinct colors, familiarity,
and realism), and two sentiment ratings (interestingness and happiness). We
curate 1142 scientific visualization (SciVis) images from the original 2231
images in published IEEE SciVis papers from 2008 to 2017 and compute
memorability scores of 228 SciVis images from data collected on Amazon
Mechanical Turk (MTurk). Results showed that the memorability of SciVis images
is mostly correlated with clutter and the number of distinct colors. We further
investigate the differences between scientific visualization and infographics
as a means to understand memorability differences by data attributes