Skip to main content

Process and Pitfalls in Writing Information Visualization Research Papers

  • Chapter
Information Visualization

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4950))

Abstract

The goal of this chapter is to help authors recognize and avoid a set of pitfalls that recur in many rejected information visualization papers, using a chronological model of the research process. Selecting a target paper type in the initial stage can avert an inappropriate choice of validation methods. Pitfalls involving the design of a visual encoding may occur during the middle stages of a project. In a later stage when the bulk of the research is finished and the paper writeup begins, the possible pitfalls are strategic choices for the content and structure of the paper as a whole, tactical problems localized to specific sections, and unconvincing ways to present the results. Final-stage pitfalls of writing style can be checked after a full paper draft exists, and the last set of problems pertain to submission.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 16.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Amar, R., Eagan, J., Stasko, J.: Low-level components of analytic activity in information visualization. In: Proc. IEEE Symposium on Information Visualization (InfoVis), pp. 111–117 (2005)

    Google Scholar 

  2. Becker, R.A., Cleveland, W.S., Shyu, M.J.: The visual design and control of trellis display. Journal of Computational and Statistical Graphics 5, 123–155 (1996)

    Article  Google Scholar 

  3. Card, S., Mackinlay, J.: The structure of the information visualization design space. In: Proc. IEEE Symposium on Information Visualization (InfoVis), pp. 92–99 (1997)

    Google Scholar 

  4. Dupré, L.: Bugs in Writing. Addison-Wesley, Reading (1995)

    Google Scholar 

  5. Fekete, J.-D., Plaisant, C.: Interactive information visualization of a million items. In: Proc. IEEE Symposium on Information Visualization (InfoVis), pp. 117–126 (2002)

    Google Scholar 

  6. Fua, Y.-H., Ward, M.O., Rundensteiner, E.A.: Hierarchical parallel coordinates for visualizing large multivariate data sets. In: Proc. IEEE Visualization Conf. (Vis), pp. 43-50 (1999)

    Google Scholar 

  7. Furnas, G., Bederson, B.: Space-scale diagrams: Understanding multiscale interfaces. In: Proc. ACM Conf. Human Factors in Computing Systems (CHI), pp. 234-241 (1995)

    Google Scholar 

  8. Furnas, G.W.: A fisheye follow-up: Further reflection on focus + context. In: Proc. ACM Conf. Human Factors in Computing Systems (CHI), pp. 999–1008 (2006)

    Google Scholar 

  9. Grossman, T., Wigdor, D., Balakrishnan, R.: Exploring and reducing the effects of orientation on text readability in volumetric displays. In: Proc. ACM Conf. Human Factors in Computing Systems (CHI), pp. 483–492 (2007)

    Google Scholar 

  10. Hachul, S., Jünger, M.: Drawing large graphs with a potential-field-based multilevel algorithm. In: Pach, J. (ed.) GD 2004. LNCS, vol. 3383, pp. 285–295. Springer, Heidelberg (2005)

    Google Scholar 

  11. Havre, S., Hetzler, B., Nowell, L.: Themeriver(tm): In search of trends, patterns, and relationships. In: Proc. IEEE Symposium on Information Visualization (InfoVis), pp. 115–123 (2000)

    Google Scholar 

  12. Healey, C.G.: Perception in visualization, cited 14 Nov. 2007, http://www.csc.ncsu.edu/faculty/healey/PP

  13. Heer, J., boyd, d.: Vizster: Visualizing online social networks. In: Proc. IEEE Symposium on Information Visualization (InfoVis), pp. 32–39 (2005)

    Google Scholar 

  14. Heer, J., Card, S.K., Landay, J.A.: prefuse: a toolkit for interactive information visualization. In: Proc. ACM Conf. Human Factors in Computing Systems (CHI), pp. 421–430 (2005)

    Google Scholar 

  15. Holten, D.: Hierarchical edge bundles: Visualization of adjacency relations in hierarchical data. IEEE Trans. Visualization and Computer Graphics (TVCG) (Proc. InfoVis 06) 12(5), 741–748 (2006)

    Article  Google Scholar 

  16. Hornbæk, K., Hertzum, M.: Untangling the usability of fisheye menus. ACM Trans. on Computer-Human Interaction (ToCHI) 14(2), article 6 (2007)

    Google Scholar 

  17. Isaacs, E., Tang, J.: Why don’t more non-North-American papers get accepted to CHI? SIGCHI Bulletin 28(1) (1996), http://www.sigchi.org/bulletin/1996.1/isaacs.html

  18. Johnson, C., Moorhead, R., Munzner, T., Pfister, H., Rheingans, P., Yoo, T.S.: NIH/NSF Visualization Research Challenges Report. IEEE Computer Society Press, Los Alamitos (2006)

    Google Scholar 

  19. Johnson, R.E., et al.: How to get a paper accepted at OOPSLA. In: Proc. Conf. Object Oriented Programming Systems Languages and Applications (OOPSLA), pp. 429–436 (1996), http://www.sigplan.org/oopsla/oopsla96/how93.html

  20. Kajiya, J.: How to get your SIGGRAPH paper rejected, http://www.siggraph.org/publications/instructions/rejected

  21. Kincaid, R., Ben-Dor, A., Yakhini, Z.: Exploratory visualization of array-based comparative genomic hybridization. Information Visualization 4(3), 176–190 (2005)

    Article  Google Scholar 

  22. Levin, R., Redell, D.D.: An evaluation of the ninth SOSP submissions; or, how (and how not) to write a good systems paper. ACM SIGOPS Operating Systems Review 17(3), 35–40 (1983), http://www.usenix.org/events/samples/submit/advice.html

    Google Scholar 

  23. MacEachren, A., Dai, X., Hardisty, F., Guo, D., Lengerich, G.: Exploring high-D spaces with multiform matrices and small multiples. In: Proc. IEEE Symposium on Information Visualization (InfoVis), pp. 31–38 (2003)

    Google Scholar 

  24. Mackinlay, J.D.: Automating the Design of Graphical Presentations of Relational Information. ACM Trans. on Graphics (TOG) 5(2), 111–141 (1986)

    Google Scholar 

  25. Munzner, T.: Drawing large graphs with H3Viewer and Site Manager. In: Whitesides, S.H. (ed.) GD 1998. LNCS, vol. 1547, pp. 384–393. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  26. Munzner, T., Burchard, P.: Visualizing the structure of the world wide web in 3D hyperbolic space. In: Proc. Virtual Reality Modelling Language Symposium (VRML), pp. 33–38. ACM SIGGRAPH (1995)

    Google Scholar 

  27. Nielsen, J.: Guerrilla HCI: Using discount usability engineering to penetrate the intimidation barrier. In: Bias, R.G., Mayhew, D.J. (eds.) Cost-justifying usability, pp. 245–272. Academic Press, London (1994)

    Google Scholar 

  28. Partridge, C.: How to increase the chances your paper is accepted at ACM SIGCOMM. ACM SIGCOMM Computer Communication Review 28(3) (1998), http://www.sigcomm.org/conference-misc/author-guide.html

  29. Plaisant, C.: The challenge of information visualization evaluation. In: Proc. Advanced Visual Interfaces (AVI), pp. 109–116 (2004)

    Google Scholar 

  30. Plumlee, M., Ware, C.: Zooming versus multiple window interfaces: Cognitive costs of visual comparisons. Proc. ACM Trans. on Computer-Human Interaction (ToCHI) 13(2), 179–209 (2006)

    Article  Google Scholar 

  31. Pousman, Z., Stasko, J.T., Mateas, M.: Casual information visualization: Depictions of data in everyday life. IEEE Trans. Visualization and Computer Graphics (TVCG) (Proc. InfoVis 07) 13(6), 1145–1152 (2007)

    Article  Google Scholar 

  32. Rogowitz, B.E., Treinish, L.A.: How not to lie with visualization. Computers In Physics 10(3), 268–273 (1996), http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm

    Google Scholar 

  33. Shaw, M.: Mini-tutorial: Writing good software engineering research papers. In: Proc. Intl. Conf. on Software Engineering (ICSE), pp. 726–736 (2003), http://www.cs.cmu.edu/~Compose/shaw-icse03.pdf

  34. Shewchuk, J.: Three sins of authors in computer science and math (1997), http://www.cs.cmu.edu/jrs/sins.html

  35. Shneiderman, B., Plaisant, C.: Strategies for evaluating information visualization tools: Multi-dimensional in-depth long-term case studies. In: Proc. AVI Workshop on BEyond time and errors: novel evaLuation methods for Information Visualization (BELIV), pp. 38–43 (2006)

    Google Scholar 

  36. Smallman, H.S., John, M.S., Oonk, H.M., Cowen, M.B.: Information availability in 2D and 3D displays. IEEE Computer Graphics and Applications (CG&A) 21(5), 51–57 (2001)

    Article  Google Scholar 

  37. Tang, D., Stolte, C., Bosch, R.: Design choices when architecting visualizations. Information Visualization 3(2), 65–79 (2004)

    Article  Google Scholar 

  38. Tory, M., Kirkpatrick, A.E., Atkins, M.S., Möller, T.: Visualization task performance with 2D, 3D, and combination displays. IEEE Trans. Visualization and Computer Graphics (TVCG) 12(1), 2–13 (2006)

    Article  Google Scholar 

  39. Trafton, J.G., Kirschenbaum, S.S., Tsui, T.L., Miyamoto, R.T., Ballas, J.A., Raymond, P.D.: Turning pictures into numbers: Extracting and generating information from complex visualizations. Intl. Journ. Human Computer Studies 53(5), 827–850 (2000)

    Article  MATH  Google Scholar 

  40. van Wijk, J.J., van Selow, E.R.: Cluster and calendar based visualization of time series data. In: Proc. IEEE Symposium on Information Visualization (InfoVis), pp. 4–9 (1999)

    Google Scholar 

  41. Ware, C.: Information Visualization: Perception for Design, 2nd edn. Morgan Kaufmann/Academic Press, London (2004)

    Google Scholar 

  42. Weaver, C., Fyfe, D., Robinson, A., Holdsworth, D.W., Peuquet, D.J., MacEachren, A.M.: Visual analysis of historic hotel visitation patterns. Information Visualization 6(1), 89–103 (2007)

    Google Scholar 

  43. Wilkinson, L., Anand, A., Grossman, R.: Graph-theoretic scagnostics. In: Proc. IEEE Symposium on Information Visualization (InfoVis), pp. 157-164 (2005)

    Google Scholar 

  44. Yost, B., North, C.: The perceptual scalability of visualization. IEEE Trans. Visualization and Computer Graphics (TVCG) (Proc. InfoVis 06) 12(5), 837–844 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Andreas Kerren John T. Stasko Jean-Daniel Fekete Chris North

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Munzner, T. (2008). Process and Pitfalls in Writing Information Visualization Research Papers. In: Kerren, A., Stasko, J.T., Fekete, JD., North, C. (eds) Information Visualization. Lecture Notes in Computer Science, vol 4950. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70956-5_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-70956-5_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70955-8

  • Online ISBN: 978-3-540-70956-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics