CandidTree: Visualizing structural uncertainty in similar hierarchies

Bongshin Lee, George G. Robertson, Mary Czerwinski, Cynthia Sims Parr

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)

Abstract

Most visualization systems fail to convey uncertainty within data. To provide a way to show uncertainty in similar hierarchies, we interpreted the differences between two tree structures as uncertainty. We developed a new interactive visualization system called CandidTree that merges two trees into one and visualizes two types of structural uncertainty: location and sub-tree structure uncertainty. Since CandidTree can visualize the differences between two tree structures, we conducted a series of user studies with tree-comparison tasks. First a usability study was conducted to identify major usability issues and evaluate how our system works. Another qualitative user study was conducted to see if biologists, who regularly work with hierarchically organized names, are able to use CandidTree, and to assess the uncertainty metric we used. A controlled experiment with software engineers was conducted to compare CandidTree with WinDiff, a traditional files and folders comparison tool. The results showed that users performed better with CandidTree. Furthermore, CandidTree received better satisfaction ratings and all users preferred CandidTree to WinDiff.

Original languageEnglish
Pages (from-to)233-246
Number of pages14
JournalInformation Visualization
Volume6
Issue number3
DOIs
Publication statusPublished - 2007 Dec

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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