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Visual Data Mining: The VisMiner Approach, 2nd Edition by Russell K. Anderson

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2

Initial Data Exploration and Dataset Preparation Using VisMiner

The Rationale for Visualizations

Studies over the past 30 years by cognitive scientists and computer graphics researchers have found two primary benefits of visualizations:

  • potentially high information density
  • rapid extraction of content due to parallel processing of an image by the human visual system.

Information density is usually defined as the number of values represented in a given area. Depending on the design, the density of visualizations can be orders of magnitude greater than textual presentations containing the same content.

In the vocabulary of cognitive science, a key component of rapid extraction of image content is usually referred to as preattentive processing. When an image is presented, the viewer's brain immediately begins extracting content from the image. In as little as 50 milliseconds it locates significant objects in the image and begins to categorize and prioritize those objects with respect to their importance to image comprehension. Researchers have identified a shortlist of visual properties that are preattentively processed – those that the brain considers to be of highest priority to which it initially directs its attention. They include: color, position, shape, motion, orientation, highlighting via addition, alignment, and lighting anomalies. When visualizations are designed using these properties, attention can be immediately drawn to targets that the designer would like the viewer ...

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