What makes a visualization memorable

IEEE Transactions on Visualization and Computer Graphics

Volumn 19, Issue 12, 2013, Pages 2306-2315

  Borkin, Michelle A ^a   Vo, Azalea A ^a   Bylinskii, Zoya ^b   Isola, Phillip ^c   Sunkavalli, Shashank ^a   Oliva, Aude ^b   Pfister, Hanspeter ^a  

^a HARVARD UNIVERSITY   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

information visualization; memorability; Visualization taxonomy

Indexed keywords

AMAZON'S MECHANICAL TURKS; DATA UNDERSTANDING; GOVERNMENT REPORTS; HUMAN COGNITION; INFORMATION VISUALIZATION; MEMORABILITY; SCIENTIFIC JOURNALS; UTILITY OF INFORMATION;

DATA VISUALIZATION; GRAPH THEORY; INFORMATION SYSTEMS;

VISUALIZATION;

ARTICLE; ARTIFICIAL INTELLIGENCE; ASSOCIATION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER INTERFACE; HUMAN; MEMORY; METHODOLOGY; PATTERN RECOGNITION; PHYSIOLOGY; TASK PERFORMANCE; PROCEDURES;

ARTIFICIAL INTELLIGENCE; CUES; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MEMORY; PATTERN RECOGNITION, VISUAL; TASK PERFORMANCE AND ANALYSIS; USER-COMPUTER INTERFACE;

EID: 84886711492     PISSN: 10772626     EISSN: None     Source Type: Journal    
DOI: 10.1109/TVCG.2013.234     Document Type: Article

References (39)

1. R. C. Anderson and J.W. Pichert. Recall of previously unrecallable information following a shift in perspective. Journal of Verbal Learning and Verbal Behavior, 17(1):1-12, 1978.
2. W. A. Bainbridge, P. Isola, and A. Oliva. The intrinsic memorability of face images (in press). Journal of Experimental Psychology: General, 2013.
3. M. Bar and M. Neta. Humans prefer curved visual objects. Psychological science, 17(8):645-648, 2006. (Pubitemid 44179871)
4. S. Bateman, R. L. Mandryk, C. Gutwin, A. Genest, D. McDine, and C. Brooks. 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, CHI '10, pages 2573-2582. ACM, 2010.
5. C. Behrens. Infodesignpatterns. http://www.niceone.org/ infodesignpatterns/index.php5, 2013.
6. J. Bertin. Semiology of graphics: diagrams, networks, maps. 1983.
7. A. F. Blackwell and T. Green. Does metaphor increase visual language usability In Visual Languages, 1999. Proceedings. 1999 IEEE Symposium on, pages 246-253. IEEE, 1999.
8. R. Borgo, A. Abdul-Rahman, F. Mohamed, P. W. Grant, I. Reppa, L. Floridi, and M. Chen. An empirical study on using visual embellishments in visualization. Visualization and Computer Graphics, IEEE Transactions on, 18(12):2759-2768, 2012.
9. T. F. Brady, T. Konkle, G. A. Alvarez, and A. Oliva. Visual long-term memory has a massive storage capacity for object details. Proceedings of the National Academy of Sciences, 105(38):14325-14329, 2008.
10. A. Cairo. The Functional Art: An Introduction to Information Graphics and Visualization. New Riders, 2013.
11. W. S. Cleveland and R. McGill. Graphical perception: Theory, experimentation, and application to the development of graphical methods. Journal of the American Statistical Association, 79(387):531-554, 1984.
12. Y. Englehardt. The language of graphics: A framework for the analysis of syntax and meaning in maps, charts and diagrams. PhD thesis, Institute for Logic, Language and Computation, University of Amsterdam, 2002.
13. S. Few. Benefitting infovis with visual difficulties Provocation without a cause. Visual Business Intelligence Newsletter, 2011.
14. S. Few. The chartjunk debate: A close examination of recent findings. Visual Business Intelligence Newsletter, 2011.
15. R. L. Harris. Information graphics: A comprehensive illustrated reference. Oxford University Press, 1999.
16. J. Heer, M. Bostock, and V. Ogievetsky. A tour through the visualization zoo. Communications of the ACM, 53(6):59-67, 2010.
17. J. Heer and B. Shneiderman. Interactive dynamics for visual analysis. Queue, 10(2):30, 2012.
18. N. Holmes. Designer's Guide to Creating Charts and Diagrams. Watson-Guptill Publications, 1984.
19. J. Hullman, E. Adar, and P. Shah. Benefitting infovis with visual difficulties. Visualization and Computer Graphics, IEEE Transactions on, 17(12):2213-2222, 2011.
20. P. Isola, D. Parikh, A. Torralba, and A. Oliva. Understanding the intrinsic memorability of images. In J. Shawe-Taylor, R. Zemel, P. Bartlett, F. Pereira, and K. Weinberger, editors, Advances in Neural Information Processing Systems (NIPS), volume 24, pages 2429-2437, 2011.
21. P. Isola, J. Xiao, A. Torralba, and A. Oliva. What makes an image memorable In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, pages 145-152. IEEE, 2011.
22. T. Konkle, T. F. Brady, G. A. Alvarez, and A. Oliva. Conceptual distinctiveness supports detailed visual long-term memory for real-world objects. Journal of experimental psychology. General, 139(3):558-578, 2010.
23. T. Konkle, T. F. Brady, G. A. Alvarez, and A. Oliva. Scene memory is more detailed than you think the role of categories in visual long-term memory. Psychological Science, 21(11):1551-1556, 2010.
24. S. M. Kosslyn. Understanding charts and graphs. Applied cognitive psychology, 3(3):185-225, 1989.
25. E. Lee. Visualizing blog: A taxonomy of data visualization. http://www.visualizing.org, 2013.
26. R. Lengler and M. J. Eppler. Towards a periodic table of visualization methods for management. In IASTED Proceedings of the Conference on Graphics and Visualization in Engineering (GVE 2007), Clearwater, Florida, USA, 2007.
27. K. Marriott, H. Purchase, M. Wybrow, and C. Goncu. Memorability of visual features in network diagrams. Visualization and Computer Graphics, IEEE Transactions on, 18(12):2477-2485, 2012.
28. W. Mason and S. Suri. Conducting behavioral research on Amazon's Mechanical Turk. Behav Res, 44:1-23, 2012.
29. O. Neurath. From hieroglyphics to Isotype: A visual autobiography. Hyphen Press, London, 2010.
30. S. Pinker. A theory of graph comprehension. Artificial intelligence and the future of testing, pages 73-126, 1990.
31. R. Reber, N. Schwarz, and P. Winkielman. Processing fluency and aesthetic pleasure: is beauty in the perceiver's processing experience Personality and social psychology review, 8(4):364-382, 2004. (Pubitemid 39665855)
32. J. C. Roberts. Display models-ways to classify visual representations. International Journal of Computer Integrated Design and Construction, 2(4):241-250, 2000.
33. J. F. Rodrigues, A. J. Traina, M. C. F. de Oliveira, and C. Traina. Reviewing data visualization: an analytical taxonomical study. In Information Visualization, 2006. IV 2006. Tenth International Conference on, pages 713-720. IEEE, 2006.
34. J. Ross, L. Irani, M. S. Silberman, A. Zaldivar, and B. Tomlinson. Who are the Crowdworkers Shifting Demographics in Mechanical Turk. CHI EA, pages 2863-2872, 2010.
35. B. Shneiderman. The eyes have it: A task by data type taxonomy for information visualizations. In Visual Languages, 1996. Proceedings., IEEE Symposium on, pages 336-343. IEEE, 1996.
36. M. Tory and T. Moller. Rethinking visualization: A high-level taxonomy. In Information Visualization, 2004. INFOVIS 2004. IEEE Symposium on, pages 151-158. IEEE, 2004. (Pubitemid 40449140)
37. E. Tufte. Envisioning Information. Cheshire (Conn.), 1990.
38. E. Tufte. The Visual Display of Quantitative Information. Cheshire (Conn.), 2001.
39. A. Vande Moere, M. Tomitsch, C. Wimmer, B. Christoph, and T. Grechenig. Evaluating the effect of style in information visualization. Visualization and Computer Graphics, IEEE Transactions on, 18(12):2739-2748, 2012.