The Community for Technology Leaders
RSS Icon
Issue No.04 - July-Aug. (2013 vol.33)
pp: 14-19
G. S. Owen , Georgia State Univ., Atlanta, GA, USA
The past 10 years have seen profound changes in visualization algorithms, techniques, methodologies, and applications. These changes are forcing alterations to visualization courses. Unfortunately, outdated course content recommendations, together with profound changes in the underlying technology and methodology, are producing an unstable ground for educators at a time when visual representations are becoming increasingly important. To address this issue, educators held meetings or workshops at Siggraph 2011 and 2012 and a panel and workshop at Eurographics 2012. This article presents the insights gathered at these events.
Data visualization, Visualization, Visual analytics, Programming profession, Algorithm design and analysis,liberal education, visualization education, computer graphics education, visualization, computer graphics, data visualization, scientific visualization, information visualization, visual analytics
G. S. Owen, G. Domik, D. S. Ebert, J. Kohlhammer, H. Rushmeier, B. S. Santos, D. Weiskopf, "How Visualization Courses Have Changed over the Past 10 Years", IEEE Computer Graphics and Applications, vol.33, no. 4, pp. 14-19, July-Aug. 2013, doi:10.1109/MCG.2013.57
1. G. Domik et al., “Visualization Curriculum Panel—or the Changes We Have Made to Our Visualization Courses over the Last 10 Years,” Eurographics 2012—Education Papers, 2012;
2. “Liberal Education,” Assoc. of Am. Colleges and Universities, 2013;
3. J. Bernard et al., “Irina: A Visual Digital Library Approach for Time-Oriented Scientific Primary Data,” Int'l J. Digital Libraries, vol. 11, no. 2, 2011 pp. 111-123.
4. N. Elmqvist and D.S. Ebert, “Leveraging Multi­disciplinarity in a Visual Analytics Graduate Course,” IEEE Computer Graphics and Applications, vol. 32, no. 3, 2012 pp. 84-87.
5. P. Dias, J. Madeira, and B. Sousa Santos, “Education: Teaching 3D Modelling and Visualization Using VTK,” Computers and Graphics, vol. 32, no. 3, 2008 pp. 363-370.
6. B. Sousa Santos et al., “Integrating User Studies into Computer Graphics-Related Courses,” IEEE Computer Graphics and Applications, vol. 31, no. 5, 2011 pp. 94-96.
7. C. Müller et al., “Large-Scale Visualization Projects for Teaching Software Engineering,” IEEE Computer Graphics and Applications, vol. 32, no. 4, 2012 pp. 14-19.
8. G. Domik, “Fostering Collaboration and Self-Motivated Learning: Best Practices in a One-Semester Visualization Course,” IEEE Computer Graphics and Applications, vol. 32, no. 1, 2012 pp. 87-91.
9. C. Ware, Information Visualization: Perception for Design, 3rd ed., Morgan Kaufmann, 2012.
10. M.O. Ward, G. Grinstein, and D. Keim, Interactive Data Visualization, AK Peters, 2010.
11. J.J. Thomas and K.A. Cook eds., , Illuminating the Path: The Research and Development Agenda for Visual Analytics, IEEE, 2005.
12. M. Bailey and S. Cunningham, Graphics Shaders: Theory and Practice, 2nd ed., AK Peters, 2011.
26 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool