Evaluating user behavior and strategy during visual exploration

ACM International Conference Proceeding Series

Volumn 10-November-2015, Issue , 2014, Pages 41-45

  Reda, Khairi ^a   Johnson, Andrew E ^b   Leigh, Jason ^c   Papka, Michael E ^d  

^a ARGONNE NATIONAL LABORATORY   (United States)

^b UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

^c UNIVERSITY OF HAWAII   (United States)

^d NORTHERN ILLINOIS UNIVERSITY   (United States)

Author keywords

Exploratory visual analysis; Insight based evaluation

Indexed keywords

VISUALIZATION;

INSIGHT-BASED EVALUATION; MICRO PATTERN; USER BEHAVIORS; USER STRATEGIES; VISUAL ANALYSIS; VISUAL EXPLORATION;

BEHAVIORAL RESEARCH;

EID: 84955454307     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2669557.2669575     Document Type: Conference Paper

References (20)

1. R. Amar, J. Eagan, and J. Stasko. Low-level com- ponents of analytic activity in information visualiza- tion. In Information Visualization, 2005. INFOVIS 2005. IEEE Symposium on, pages 111-117. IEEE, 2005.
2. W. S. Cleveland. The Elements of Graphing Data. Wadsworth Advanced Books and Software, 1985.
3. K. Ericsson and H. Simon. Protocol analysis: Verbal reports as data. MIT Press, revised edition, 1993.
4. T. Green, W. Ribarsky, and B. Fisher. Building and applying a human cognition model for visual analytics. Information Visualization, 8(1): 1-13, 2009.
5. C. G. Healey and J. T. Enns. Attention and visual memory in visualization and computer graphics. Visu- alization and Computer Graphics, IEEE Transactions on, 18(7): 1170-1188, 2012.
6. H. Lam. A framework of interaction costs in informa- tion visualization. Visualization and Computer Graph- ics, IEEE Transactions on, 14(6): 1149-1156, 2008.
7. Z. Liu and J. T. Stasko. Mental models, visual reason- ing and interaction in information visualization: A top- down perspective. Visualization and Computer Graph- ics, IEEE Transactions on, 16(6): 999-1008, 2010.
8. E. Mayr, M. Smuc, and H. Risku. Many roads lead to rome: Mapping users' problem-solving strategies. In- formation Visualization, 10(3): 232-247, 2011.
9. C. North. Toward measuring visualization insight. Computer Graphics and Applications, IEEE, 26(3): 6-9, 2006.
10. P. Parsons and K. Sedig. Distribution of information processing while performing complex cognitive activi- ties with visualization tools. In Handbook of Human Centric Visualization, pages 693-715. Springer, 2014.
11. M. Pohl, S. Wiltner, and S. Miksch. Exploring informa- tion visualization: Describing different interaction pat- terns. In Proceedings of the 3rd BELIV'10 Workshop: BEyond time and errors: Novel evaLuation methods for Information Visualization, pages 16-23. ACM, 2010.
12. H. C. Purchase, E. Hoggan, and C. Görg. How impor- tant is the \mental map"?-an empirical investigation of a dynamic graph layout algorithm. In Graph Drawing, pages 184-195. Springer, 2007.
13. K. Reda, A. Febretti, A. Knoll, J. Aurisano, J. Leigh, A. Johnson, M. Papka, and M. Hereld. Visualizing large, heterogeneous data in hybrid-reality environ- ments. Computer Graphics and Applications, 33(4): 38-48, 2013.
14. K. Reda, A. Johnson, V. Mateevitsi, C. Offord, and J. Leigh. Scalable visual queries for data exploration on large, high-resolution 3d displays. In SC Compan- ion: High Performance Computing, Networking, Stor- age and Analysis, pages 196-205. IEEE, 2012.
15. K. Reda, C. Offord, A. Johnson, and J. Leigh. Ex- panding the porthole: Leveraging large, high-resolution displays in exploratory visual analysis. In CHI'14 EA on Human Factors in Computing Systems, pages 2047- 2052. ACM, 2014.
16. P. Saraiya, C. North, and K. Duca. An insight-based methodology for evaluating bioinformatics visualiza- tions. Visualization and Computer Graphics, IEEE Transactions on, 11(4): 443-456, 2005.
17. K. Sedig and P. Parsons. Interaction design for com- plex cognitive activities with visual representations: A pattern-based approach. AIS Transactions on Human- Computer Interaction, 5(2): 84-133, 2013.
18. L. Shupp, C. Andrews, M. Dickey-Kurdziolek, B. Yost, and C. North. Shaping the display of the future: The effects of display size and curvature on user perfor- mance and insights. Human-Computer Interaction, 24(1-2): 230-272, 2009.
19. A. Treisman. Features and objects in visual processing. Scientific American, 255(5): 114-125, 1986.
20. J. W. Tukey. We need both exploratory and confirma- tory. The American Statistician, 34(1): 23-25, 1980.