Abstract
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 language | English |
|---|---|
| Article number | 09 |
| Pages (from-to) | 77-86 |
| Number of pages | 10 |
| Journal | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 5669 |
| DOIs | |
| State | Published - 20 Jul 2005 |
| Event | Proceedings of SPIE-IS and T Electronic Imaging - Visualization and Data Analysis 2005 - San Jose, CA, United States Duration: 17 Jan 2005 → 18 Jan 2005 |
Keywords
- 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