Visualizing the effects of scale and geography in multivariate comparison

Sarah Goodwin, Jason Dykes, Aidan Slingsby

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

4 Citations (Scopus)


Our research investigates the sensitivities and complexities of visualizing multivariate data over multiple scales with the consideration of local geography. We investigate this in the context of creating geodemographic classifications, where multivariate comparison for the variable selection process is an important, yet time-consuming and intensive process. We propose a visual interactive approach which allows skewed variables and those with strong correlations to be quickly identified and investigated and the geography of multi-scale correlation to be explored. Our objective is to present comprehensive documentation of the parameter space prior to the development of the visualization tools to help explore it.

Original languageEnglish
Title of host publication2014 IEEE Conference on Visual Analytics Science and Technology
EditorsMin Chen, David Ebert, Chris North
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages2
ISBN (Electronic)9781479962273
Publication statusPublished - 2014
Externally publishedYes
EventIEEE Conference on Visual Analytics Science and Technology 2014 - Paris, France
Duration: 9 Oct 201414 Oct 2014


ConferenceIEEE Conference on Visual Analytics Science and Technology 2014
Abbreviated titleVAST 2014
Internet address


  • D.2.2 [Software Engineering]: Design Tools and Techniques
  • I.5.2 [Pattern Recognition]: Design Methodology - Feature Evaluation and Selection

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