The Impact of Clutter on the Comprehension of Set Visualizations

  • Mohanad Alqadah

Student thesis: Doctoral Thesis


The aim of this research is to determine the effect of visual clutter or complexity on the comprehension of set visualizations. Existing research found that it is important to understand visual clutter to draw effective diagrams. Euler diagrams have long been used to visualize sets, using closed curves to show relationships. Euler diagrams can be an effective representation of information, but they can become cluttered. Previous research established a measure of Euler diagram clutter, empirically shown to correspond with how people perceive clutter. However, the effect of clutter on users’ understanding was unknown. Moreover, it was unknown whether using two less cluttered Euler diagrams to represent information is more effective than using a single more cluttered diagram.

In the first contribution of this thesis, we established that clutter has a significant effect on task performance: increased clutter in Euler diagrams leads to significantly worse performance. In addition, we found a significant effect of zone (a region in the
diagram) clutter, in Euler diagrams, on task performance. The zones with a medium and a high level of clutter were the worst for task performance as compared to the zones with low clutter. To establish a method for managing the effect of clutter, we proposed representing information using multiple Euler diagrams. To establish the effectiveness of this method, we empirically evaluated task performance comparing a single diagram with the same information represented in two diagrams. This confirmed that using two diagrams better supported task performance than using a single diagram where at least six sets were represented.

An alternative visualization of sets is provided by linear diagrams which use line segments instead of closed curves. Prior to this thesis, there was no insight into what constituted a visually complex linear diagram or the effect of complexity on task performance. This thesis defined four different measures of visual complexity for linear diagrams. We empirically established that counting the number of line segments best matched participants’ perception of visual complexity. We followed up on this insight by empirically establishing that the time taken to perform tasks strongly correlates with the position of the relevant information in the linear diagram, and there was no evidence that visual complexity has a significant effect on task performance, unlike Euler diagrams. This shows that it is important to understand the effect of visual complexity for each visualization because its effect is notation dependent. However, we still found, in a further study, that using multiple linear diagrams supported significantly better task performance than single diagrams for six or more sets. Therefore, this thesis sheds light on the effect of visual clutter or complexity not only for two very different visualizations of sets, namely Euler diagrams and linear diagrams, but for visualization generally.
Date of AwardJul 2018
Original languageEnglish
Awarding Institution
  • University of Brighton
SupervisorGem Stapleton (Supervisor), John Howse (Supervisor) & Peter Chapman (Supervisor)

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