The Aesthetics of Diagrams

Michael Burch

2015

Abstract

Diagrammatic representations are omnipresent and are used in various application domains. One of their major goal, in particular for information visualization, is to make data visual in a way that a spectator can easily understand the graphical encoding to finally derive insights from the data. As we see, there are various different ways to visually depict data by using visual features in various combinations. In this paper we come up with some thoughts about existing diagram styles, for which we first discuss the benefits and drawbacks of each of them focusing on aesthetics based on readability. Additionally, we describe some initial results on the aesthetics of diagrams which we recorded in a web-based experiment. In this, we asked participants to vote for one of two given diagrams of a given repertoire of 70 of them covering all examined aspects which focuses more on aesthetics in the sense of beauty, not readability. The major result of this experiment unhides a trend towards colored, 3D, and radial diagrams which stands somewhat in contrast to readability user studies in information visualization oftentimes tending towards 2D and Cartesian diagrams for data exploration.

References

  1. Bar, M. and Neta, M. (2006). Humans prefer curved visual objects. Psychological Science, 17(8):645-648.
  2. Bateman, S., Mandryk, R. L., Gutwin, C., Genest, A., McDine, D., and Brooks, C. A. (2010). Useful junk?: the effects of visual embellishment on comprehension and memorability of charts. In Proceedings of the 28th International Conference on Human Factors in Computing Systems, pages 2573-2582.
  3. Beck, F., Burch, M., Diehl, S., and Weiskopf, D. (2014). The state of the art in visualizing dynamic graphs. In EuroVis State-of-the-Art Reports, EuroVis STAR.
  4. Bennett, C., Ryall, J., Spalteholz, L., and Gooch, A. (2007). The aesthetics of graph visualization. In Proceedings of Eurographics Workshop on Computational Aesthetics in Graphics, Visualization and Imaging, pages 57- 64.
  5. Bertin, J. (2010). Semiology of Graphics - Diagrams, Networks, Maps. ESRI.
  6. Burch, M., Andrienko, G. L., Andrienko, N. V., Höferlin, M., Raschke, M., and Weiskopf, D. (2013). Visual task solution strategies in tree diagrams. In Proceedings of IEEE Pacific Visualization Symposium, pages 169-176.
  7. Burch, M. and Diehl, S. (2008). TimeRadarTrees: Visualizing Dynamic Compound Digraphs. Computer Graphics Forum, 27(3):823-830.
  8. Draper, G. M., Livnat, Y., and Riesenfeld, R. F. (2009). A Survey of Radial Methods for Information Visualization. IEEE Transactions on Visualization and Computer Graphics, 15(5):759-776.
  9. Harel, D. (1997). On the aesthetics of diagrams. In Proceedings of the Symposium on Visual Languages, pages 128-130.
  10. Heinrich, J., Burch, M., and O'Donoghue, S. (2014). On the use of 1D, 2D, and 3D visualization for molecular graphics. In Proceedings of 3D Visualization Workshop@IEEE VIS.
  11. Huang, W. (2007). Using eye tracking to investigate graph layout effects. In APVIS 2007, 6th International AsiaPacific Symposium on Visualization, pages 97-100.
  12. Kleiberg, E., Wetering, H. V. D., and Wijk, J. J. V. (2001). Botanical visualization of huge hierarchies. In Proceedings of the IEEE Symposium on Information Visualization, pages 87-94. Society Press.
  13. Purchase, H. C. (2014). Twelve years of diagrams research. Journal on Visual Languages and Computing, 25(2):57-75.
  14. Rojas, R. (1998). How to make Zuse's Z3 a universal computer. IEEE Annals of the History of Computing, 20(3):51-54.
  15. Rosenholtz, R., Li, Y., Mansfield, J., and Jin, Z. (2005). Feature congestion: a measure of display clutter. In Proceedings of Conference on Human Factors in Computing Systems, pages 761-770.
  16. Tufte, E. R. (1983). The Visual Display of Quantitative Information. Graphics Press, Cheshire, CT.
  17. Tufte, E. R. (1990). Envisioning Information. Graphics Press, Cheshire, CT.
  18. Tversky, B., Morrison, J. B., and Bétrancourt, M. (2002). Animation: can it facilitate? International Journal on Human-Computer Studies, 57(4):247-262.
  19. van Wijk, J. J. (2005). The value of visualization. In Proceedings of 16th IEEE Visualization Conference (VIS 2005), pages 11-18.
  20. Ware, C. (2000). Information Visualization: Perception for Design. Academic Press, San Diego, CA, USA.
  21. Ware, C., Purchase, H. C., Colpoys, L., and McGill, M. (2002). Cognitive measurements of graph aesthetics. Information Visualization, 1(2):103-110.
  22. Wettel, R. and Lanza, M. (2007). Visualizing software systems as cities. In Proceedings of the 4th IEEE International Workshop on Visualizing Software for Understanding and Analysis, pages 92-99.
  23. Zangwill, N. (2008). Aesthetic Judgment. Stanford Encyclopedia of Philosophy.
Download


Paper Citation


in Harvard Style

Burch M. (2015). The Aesthetics of Diagrams . In Proceedings of the 6th International Conference on Information Visualization Theory and Applications - Volume 1: IVAPP, (VISIGRAPP 2015) ISBN 978-989-758-088-8, pages 262-267. DOI: 10.5220/0005357502620267


in Bibtex Style

@conference{ivapp15,
author={Michael Burch},
title={The Aesthetics of Diagrams},
booktitle={Proceedings of the 6th International Conference on Information Visualization Theory and Applications - Volume 1: IVAPP, (VISIGRAPP 2015)},
year={2015},
pages={262-267},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005357502620267},
isbn={978-989-758-088-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Information Visualization Theory and Applications - Volume 1: IVAPP, (VISIGRAPP 2015)
TI - The Aesthetics of Diagrams
SN - 978-989-758-088-8
AU - Burch M.
PY - 2015
SP - 262
EP - 267
DO - 10.5220/0005357502620267