Orca: A visualization toolkit for high-dimensional data

Peter Sutherland, Anthony Rossini, Thomas Lumley, Nicholas Lewin-Koh, Julie Dickerson, Zach Cox, Dianne Cook

Research output: Contribution to journalArticleResearchpeer-review

17 Citations (Scopus)

Abstract

This article describes constructing interactive and dynamic linked data views using the Java programming language. The data views are designed for data that have a multivariate component. The approach to displaying data comes from earlier research on building statistical graphics based on data pipelines, in which different aspects of data processing and graphical rendering are organized conceptually into segments of a pipeline. The software design takes advantage of the object-oriented nature of the Java language to open up the data pipeline, allowing developers to have greater control over their visualization applications. Importantly, new types of data views coded to adhere to a few simple design requirements can easily be integrated with existing pipe sections. This allows access to sophisticated linking and dynamic interaction across all (new and existing) view types. Pipe segments can be accessed from data analysis packages such as Omegahat or R, providing a tight coupling of visual and numerical methods.he proposed method.

Original languageEnglish
Pages (from-to)509-529
Number of pages21
JournalJournal of Computational and Graphical Statistics
Volume9
Issue number3
DOIs
Publication statusPublished - 1 Jan 2000
Externally publishedYes

Keywords

  • Brushing
  • Compositional data
  • Data projections
  • Dynamic graphics
  • Interactive graphics
  • Java
  • Motion graphics
  • Multiple linked views
  • Multivariate space-time data
  • Object-oriented software
  • Plot matrices

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