Conditioned and manipulable matrix for visual exploration

  • Authors:
  • Xiping Dai;Frank Hardisty

  • Affiliations:
  • University park, PA;University park, PA

  • Venue:
  • dg.o '02 Proceedings of the 2002 annual national conference on Digital government research
  • Year:
  • 2002

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Abstract

As the size and complexity of federal statistical summaries increase and accumulate, the development of quality graphics for data visualization and exploration attracts increasing research effort. While some research has focused on new designs for visual presentation and exploration of highly multivariate data (Fua et. al., 1999), a reconsideration of perceptual and cognitive factors leads us to another approach to improve users' ability to extract information based on traditional statistical graph and map representations. With effective interfaces and interaction techniques, users can maximize information obtained from familiar and easy-use exploratory statistical graphs.