SizePairs: Achieving Stable and Balanced Temporal Treemaps using Hierarchical Size-based Pairing

Chang Han, Jaemin Jo, Anyi Li, Bongshin Lee, Oliver Deussen, Yunhai Wang

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

We present SizePairs, a new technique to create stable and balanced treemap layouts that visualize values changing over time in hierarchical data. To achieve an overall high-quality result across all time steps in terms of stability and aspect ratio, SizePairs employs a new hierarchical size-based pairing algorithm that recursively pairs two nodes that complement their size changes over time and have similar sizes. SizePairs maximizes the visual quality and stability by optimizing the splitting orientation of each internal node and flipping leaf nodes, if necessary. We also present a comprehensive comparison of SizePairs against the state-of-the-art treemaps developed for visualizing time-dependent data. SizePairs outperforms existing techniques in both visual quality and stability, while being faster than the local moves technique.

Original languageEnglish
Pages (from-to)193-202
Number of pages10
JournalIEEE Transactions on Visualization and Computer Graphics
Volume29
Issue number1
DOIs
Publication statusPublished - 2023 Jan 1

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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