Scatterplot layout for high-dimensional data visualization

Yunzhu Zheng, Haruka Suematsu, Takayuki Itoh, Ryohei Fujimaki, Satoshi Morinaga, Yoshinobu Kawahara

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)


Abstract: Multi-dimensional data visualization is an important research topic that has been receiving increasing attention. Several techniques that apply scatterplot matrices have been proposed to represent multi-dimensional data as a collection of two-dimensional data visualization spaces. Typically, when using the scatterplot-based approach it is easier to understand relations between particular pairs of dimensions, but it often requires too large display spaces to display all possible scatterplots. This paper presents a technique to display meaningful sets of scatterplots generated from high-dimensional datasets. Our technique first evaluates all possible scatterplots generated from high-dimensional datasets, and selects meaningful sets. It then calculates the similarity between arbitrary pairs of the selected scatterplots, and places relevant scatterplots closer together in the display space while they never overlap each other. This design policy makes users easier to visually compare relevant sets of scatterplots. This paper presents algorithms to place the scatterplots by the combination of ideal position calculation and rectangle packing algorithms, and two examples demonstrating the effectiveness of the presented technique.

Original languageEnglish
Pages (from-to)111-119
Number of pages9
JournalJournal of Visualization
Issue number1
Publication statusPublished - Feb 2014
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Condensed Matter Physics
  • Electrical and Electronic Engineering


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