Visual quality metrics

ABSTRACT

The definition and usage of quality metrics for Information Visualization techniques is still an immature field. Several proposals are available but a common view and understanding of this issue is still missing. This paper attempts a first step toward a visual quality metrics systematization, providing a general classification of both metrics and usage purposes. Moreover, the paper explores a quite neglected class of visual quality metrics, namely Feature Preservation Metrics, that allow for evaluating and improving in a novel way the effectiveness of basic Infovis techniques.

REFERENCES

• 1: Benjamin B. Bederson , Ben Shneiderman , Martin Wattenberg, Ordered and quantum treemaps: Making effective use of 2D space to display hierarchies, ACM Transactions on Graphics (TOG), v.21 n.4, p.833-854, October 2002 [doi>10.1145/571647.571649]
• 2: E. Bertini and G. Santucci. Give chance a chance: modeling density to enhance scatter plot quality through random data sampling. Information visualization, to appear, 2006.
• 3: S. K. Card , J. Mackinlay, The structure of the information visualization design space, Proceedings of the 1997 IEEE Symposium on Information Visualization (InfoVis '97), p.92, October 18-25, 1997
• 4: Daniel A. Keim, Designing Pixel-Oriented Visualization Techniques: Theory and Applications, IEEE Transactions on Visualization and Computer Graphics, v.6 n.1, p.59-78, January 2000 [doi>10.1109/2945.841121]
• 5: Wei Peng , Matthew O. Ward , Elke A. Rundensteiner, Clutter Reduction in Multi-Dimensional Data Visualization Using Dimension Reordering, Proceedings of the IEEE Symposium on Information Visualization (INFOVIS'04), p.89-96, October 10-12, 2004 [doi>10.1109/INFOVIS.2004.15]
• 6: Wei Peng , Matthew O. Ward , Elke A. Rundensteiner, Clutter Reduction in Multi-Dimensional Data Visualization Using Dimension Reordering, Proceedings of the IEEE Symposium on Information Visualization (INFOVIS'04), p.89-96, October 10-12, 2004 [doi>10.1109/INFOVIS.2004.15]
• 7: B. Richard. Concept demonstration: Metrics for effective information visualization. In Proc. of IEEE Symposium on Information Visualization, pages 108--111. IEEE Service Center, Phoenix, AZ, 1997.
• 8: Edward R. Tufte, The visual display of quantitative information, Graphics Press, Cheshire, CT, 1986
• 9: C. Ware. Information visualization: perception for design. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 2000.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.2 User Interfaces (D.2.2, H.1.2, I.3.6)
          Subjects: Evaluation/methodology

Additional Classification:
  I. Computing Methodologies
  I.5 PATTERN RECOGNITION
      I.5.2 Design Methodology
          Subjects: Feature evaluation and selection
  I.6 SIMULATION AND MODELING
      I.6.8 Types of Simulation
          Subjects: Visual

  K. Computing Milieux
  K.6 MANAGEMENT OF COMPUTING AND INFORMATION SYSTEMS
      K.6.4 System Management
          Subjects: Quality assurance

General Terms:
Design, Measurement, Performance