Understanding Barriers to Network Exploration with Visualization: A Report from the Trenches

Mashael Alkadi, Vanessa Serrano, James Scott-Brown, Catherine Plaisant, Jean-Daniel Fekete, Uta Hinrichs, Benjamin Bach

Research output: Contribution to journalArticlepeer-review


This article reports on an in-depth study that investigates barriers to network exploration with visualizations. Network
visualization tools are becoming increasingly popular, but little is known about how analysts plan and engage in the visual exploration
of network data—which exploration strategies they employ, and how they prepare their data, define questions, and decide on visual
mappings. Our study involved a series of workshops, interaction logging, and observations from a 6-week network exploration course.
Our findings shed light on the stages that define analysts’ approaches to network visualization and barriers experienced by some
analysts during their network visualization processes. These barriers mainly appear before using a specific tool and include defining
exploration goals, identifying relevant network structures and abstractions, or creating appropriate visual mappings for their network
data. Our findings inform future work in visualization education and analyst-centered network visualization tool design
Original languageEnglish
Pages (from-to)907-917
Number of pages11
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number1
Early online date26 Sep 2022
Publication statusPublished - 1 Jan 2023


  • Network Exploration
  • Network Visualization
  • Qualitative Study


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