Benefitting InfoVis with visual difficulties

Jessica Hullman*, Eytan Adar, Priti Shah

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

64 Scopus citations


Many well-cited theories for visualization design state that a visual representation should be optimized for quick and immediate interpretation by a user. Distracting elements like decorative "chartjunk" or extraneous information are avoided so as not to slow comprehension. Yet several recent studies in visualization research provide evidence that non-efficient visual elements may benefit comprehension and recall on the part of users. Similarly, findings from studies related to learning from visual displays in various subfields of psychology suggest that introducing cognitive difficulties to visualization interaction can improve a user's understanding of important information. In this paper, we synthesize empirical results from cross-disciplinary research on visual information representations, providing a counterpoint to efficiency-based design theory with guidelines that describe how visual difficulties can be introduced to benefit comprehension and recall. We identify conditions under which the application of visual difficulties is appropriate based on underlying factors in visualization interaction like active processing and engagement. We characterize effective graph design as a trade-off between efficiency and learning difficulties in order to provide Information Visualization (InfoVis) researchers and practitioners with a framework for organizing explorations of graphs for which comprehension and recall are crucial. We identify implications of this view for the design and evaluation of information visualizations.

Original languageEnglish (US)
Article number064986
Pages (from-to)2213-2222
Number of pages10
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number12
StatePublished - Nov 15 2011


  • Desirable difficulites
  • active processing
  • cognitive efficiency
  • engagement
  • individual differences

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design


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