Visualising high-dimensional data in time and space: Ideas from the Orca project

Thomas Lumley, Peter Sutherland, Anthony Rossini, Nicholas Lewin-Koh, Di Cook, Zach Cox

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Environmental data are frequently high-dimensional with measurements of multiple chemical constituents, plant or animal species, or meteorological variables. Environmental data are also frequently structured with interest in the patterns of variation over time and space. We describe some new data visualization methods from the Orca project that allow the analyst to reduce the dimension of the data without obscuring its basic structure and illustrate these on air pollution data.

Original languageEnglish
Pages (from-to)189-195
Number of pages7
JournalChemometrics and Intelligent Laboratory Systems
Volume60
Issue number1-2
DOIs
Publication statusPublished - 28 Jan 2002
Externally publishedYes

Keywords

  • High-dimensional data
  • Orca project
  • Visualization

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