A Review and Collation of Graphical Perception Knowledge for Visualization Recommendation
A Review and Collation of Graphical Perception Knowledge for Visualization Recommendation
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Date
2023-04-23
Authors
Zeng, Zhua
Battle, Leilani
Advisor
Citation
Zehua Zeng and Leilani Battle. 2023. A Review and Collation of Graphical Perception Knowledge for Visualization Recommendation. In CHI ’23: ACM CHI Conference on Human Factors in Computing Systems, April 23-28, 2023, Hamburg, Germany. ACM, New York, NY, USA, 16 pages.
Abstract
Selecting appropriate visual encodings is critical to designing effective visualization recommendation systems, yet few findings
from graphical perception are typically applied within these systems. We observe two significant limitations in translating graphical
perception knowledge into actionable visualization recommendation rules/constraints: inconsistent reporting of findings and a lack
of shared data across studies. How can we translate the graphical perception literature into a knowledge base for visualization
recommendation? We present a review of 59 papers that study
user perception and performance across ten visual analysis tasks.
Through this study, we contribute a JSON dataset that collates existing theoretical and experimental knowledge and summarizes
key study outcomes in graphical perception. We illustrate how this
dataset can inform automated encoding decisions with three representative visualization recommendation systems. Based on our
findings, we highlight open challenges and opportunities for the
community in collating graphical perception knowledge for a range
of visualization recommendation scenarios.