CoInsight: Visual Storytelling for Hierarchical Tables with Connected Insights

Guozheng Li, Runfei Li, Yunshan Feng, Yu Zhang, Yuyu Luo*, Chi Harold Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Extracting data insights and generating visual data stories from tabular data are critical parts of data analysis. However, most existing studies primarily focus on tabular data stored as flat tables, typically without leveraging the relations between cells in the headers of hierarchical tables. When properly used, rich table headers can enable the extraction of many additional data stories. To assist analysts in visual data storytelling, an approach is needed to organize these data insights efficiently. In this work, we propose CoInsight, a system to facilitate visual storytelling for hierarchical tables by connecting insights. CoInsight extracts data insights from hierarchical tables and builds insight relations according to the structure of table headers. It further visualizes related data insights using a nested graph with edge bundling. We evaluate the CoInsight system through a usage scenario and a user experiment. The results demonstrate the utility and usability of CoInsight for converting data insights in hierarchical tables into visual data stories.

Original languageEnglish
Pages (from-to)3049-3061
Number of pages13
JournalIEEE Transactions on Visualization and Computer Graphics
Volume30
Issue number6
DOIs
Publication statusPublished - 1 Jun 2024

Keywords

  • Data insight
  • hierarchical table
  • table data visualization
  • tabular data
  • visual storytelling

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