Effects of cognitive styles and data-characteristics on visual data mining

Peter Bak, Joachim Meyer

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


The study reports an experiment intended to identify parameters that affect the detection of cause and effect relations in graphically displayed data in a visual data mining environment. Accuracy of performance was measured as a function of visual properties of the cause function and information processing styles. People with different styles employ different task-solving-strategies, expressed by tool usage, and by effects of different visual properties of the displayed data. Participants with high analytic cognitive styles were better able to detect cause and effect relations through investigations of visual and more global properties of the displayed data. Visual properties of the data affected users with high analytic and low experiential cognitive styles similarly and had no direct effect on accuracy. The study points to the need for further research to gain a deeper understanding of the effect of user characteristics, display properties and data structure in a visual data mining environment that is based on intensive interaction of the user with complex graphical displays.

Original languageEnglish
Article number09
Pages (from-to)77-86
Number of pages10
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 20 Jul 2005
EventProceedings of SPIE-IS and T Electronic Imaging - Visualization and Data Analysis 2005 - San Jose, CA, United States
Duration: 17 Jan 200518 Jan 2005


  • Cognitive styles
  • Graphic displays
  • Visual data mining

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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