Redundant encoding strengthens segmentation and grouping in visual displays of data

Christine Nothelfer*, Michael Gleicher, Steven Franconeri

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

The availability and importance of data are accelerating, and our visual system is a critical tool for understanding it. The research field of data visualization seeks design guidelines- often inspired by perceptual psychology-for more efficient visual data analysis. We evaluated a common guideline: When presenting multiple sets of values to a viewer, those sets should be distinguished not just by a single feature, such as color, but redundantly by multiple features, such as color and shape. Despite the broad use of this practice across maps and graphs, it may carry costs, and there is no direct evidence for a benefit. We show that this practice can indeed yield a large benefit for rapidly segmenting objects within a dense display (Experiments 1 and 2), and strengthening visual grouping of display elements (Experiment 3). We predict situations where this benefit might be present, and discuss implications for models of attentional control.

Original languageEnglish (US)
Pages (from-to)1667-1676
Number of pages10
JournalJournal of Experimental Psychology: Human Perception and Performance
Volume43
Issue number9
DOIs
StatePublished - Sep 2017

Keywords

  • Data visualization
  • Feature-based attention
  • Grouping
  • Segmentation
  • Visual attention

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)
  • Behavioral Neuroscience

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