Grouping Effect for Bar Graph Summarization for People with Visual Impairments

Banri Kakehi, Masakazu Iwamura, Kazunori Minatani, Koichi Kise

Abstract: When communicating numerical data to people with visual impairments (PVI), summaries provided by current data visualization solutions tend to lose important information during summarization. To address this issue, our work focuses on summarization through bar grouping in bar graphs. Neither the effect of grouping nor the appropriate granularity of grouping has been discussed so far. Therefore, we investigate the cognitive effects of grouping and its relationship to the number of groups. A user study involving nine PVI (five blind and four with low vision) revealed that summarization through bar grouping conveys information significantly more accurately compared to simply reading individual data points, despite the inherent error produced by grouping. Additionally, we propose a cognitive error model to explain the characteristics of the observed errors.