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The ITS2 Database
16:17

The ITS2 Database

Published on: March 12, 2012

Hi-trees and their layout.

Kim Marriott1, Peter Sbarski, Tim van Gelder

  • 1Clayton School of IT, Monash University, Wellington Rd, Clayton, Vic 3800, Australia. kim.marriott@infotech.monash.edu.au

IEEE Transactions on Visualization and Computer Graphics
|January 15, 2011
PubMed
Summary
This summary is machine-generated.

We developed hi-trees, a novel visual method for displaying hierarchical data using containment or links. This representation enhances understanding of complex data structures in applications like argument mapping.

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Area of Science:

  • Computer Science
  • Data Visualization
  • Human-Computer Interaction

Background:

  • Hierarchical data is prevalent in various domains, posing challenges for effective visualization.
  • Existing tree visualization methods may not adequately represent complex relationships or scale to large datasets.

Purpose of the Study:

  • To introduce hi-trees, a new visual representation for hierarchical data.
  • To develop algorithms for drawing hi-trees using standard and novel layout techniques.
  • To demonstrate the utility of hi-trees in practical applications.

Main Methods:

  • Defined hi-trees as a hybrid visual representation using containment and links for parent-child relationships.
  • Adapted standard layered drawing conventions and bottom-up tree layout algorithms for hi-trees.
  • Explored and developed algorithms for compact layout styles for larger hi-trees.

Main Results:

  • Established a drawing convention for hi-trees based on rooted tree layouts.
  • Extended existing tree layout algorithms to accommodate the hybrid nature of hi-trees.
  • Presented algorithms for generating compact layouts suitable for large-scale hierarchical data.

Conclusions:

  • Hi-trees offer a flexible and effective visual representation for diverse hierarchical data.
  • The developed algorithms enable efficient drawing and layout of hi-trees.
  • Hi-trees show promise for applications in argument mapping and business decision support.