Information visualization

Wiley Interdisciplinary Reviews: Computational Statistics

Volumn 2, Issue 4, 2010, Pages 387-403

  Chen, Chaomei ^a  

^a Drexel University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FUNDAMENTAL CONCEPTS; INFORMATION VISUALIZATION;

INFORMATION ANALYSIS; VISUALIZATION;

INFORMATION SYSTEMS;

EID: 78651557395     PISSN: 19395108     EISSN: 19390068     Source Type: Journal    
DOI: 10.1002/wics.89     Document Type: Review

References (83)

1. Baker MP, Bushell C. After the storm: considerations for information visualization. IEEE Comput Graph Appl 1995, 15:12-15.
2. Wise JA, Thomas JJ, Pennock K, Lantrip D, Pottier M, Schur A, Crow V. Visualizing the non-visual: Spatial analysis and interaction with information from text documents. Proceedings of IEEE Symposium on Information Visualization '95, Atlanta, Georgia, USA, 1995, 51-58.
3. Chi EH. A taxonomy of visualization techniques using the data state reference model. Proceedings of Info-Vis, 2000, Salt Lake City, UT, October 9-10, 2000, (pp. 69-75) .
4. Gaviria AR. When is information visualization art? determining the critical criteria. Leonardo 2008, 41:479-482.
5. Bertin J. Semiology of Graphics: Diagrams, Networks, Maps. Wisconsin: University of Wisconsin Press; 1983.
6. ClevelandWS, McGill R. Graphical perception: theory, experimentation, and application to the development of graphical methods. J Am Stat Assoc 1984, 79: 531-553.
7. Mackinlay JD. Automating the design of graphical presentations of relational information.ACMTransGraph 1986, 5:110-141.
8. Chang R, Ziemkiewicz C, Green TM, Ribarsky W. Defining insight for visual analytics. IEEE Comput Graph Appl 2009, 29:14-17.
9. North C. Towards measuring visualization insight. IEEE Comput Graph Appl 2006, 26:6-9.
10. Chen C. An information-theoretic view of visual analytics. IEEE Comput Graph Appl 2008, 28:18-23.
11. Heer J, Viegas FB, Wattenberg M. Voyagers and voyeurs: supporting asynchronous collaborative visualization. Commun ACM 2009, 52:87-97.
12. Bush V. As we may think. Atlantic Monthly 1945, 176:101-108.
13. Plaisant C, Fekete J, Grinstein G. Promoting insight based evaluation of visualizations: from contest to benchmark repository. IEEE Trans Vis Comput Graph 2008, 14:120-134.
14. Friendly M. A brief history of data visualization. In: Chen C, Härdle W, Unwin A, eds. Handbook of Computational Statistics: Data Visualization, vol.3. Heidelberg: Springer; 2007, 1-34.
15. FriendlyM, Denis DJ. (2001, Oct 16, 2008).Milestones in the history of thematic cartography, statistical graphics, and data visualization: An illustrated chronology of innovations Retrieved March 30, 2009, from http://www.math.yorku.ca/SCS/Gallery/milestone/milestone.pdf
16. Furnas GW. Generalized fisheye views. In Proceedings of CHI '86, 1986, 16-23.
17. Tufte ER. The Visual Display of Quantitative Information. Cheshire, CT: Graphics Press; 1983.
18. Inselberg A. The Planewith ParallelCoordinates. Visual Computer 1985, 1:69-91.
19. Wegman E. Hyperdimensional Data Analysis Using Parallel Coordinates. J Am Stat Assoc 1990, 85: 664-675.
20. Johnson B, Shneiderman B. Tree-maps: A space filling approach to the visualization of hierarchical information structures. In Proceedings of IEEE Visualization 1991, 91, 284-291.
21. Eades P. A heuristic for graph drawing. Congressus Numerantium 1984, 42:149-160.
22. Fruchterman TMJ, Reingold EM. Graph drawing by force-directed placement. Software- Practice and Experience 1991, 21:1129-1164.
23. Kamada T, Kawai S. A general framework for visualizing abstract objects and relations. ACM Trans Graph 1991, 10:1-39.
24. Dwyer T, Marriott K, Schreiber F, Stuckey PJ, Woodward M, Wybrow M. Exploration of networks using overview+detail with constraint-based cooperative layout. IEEE Trans Vis Comput Graph 2008, 14:1293-1300.
25. Fairchild K, Poltrock S, Furnas G. SemNet: Threedimensional graphic representations of large knowledge bases. In:Guidon R, ed. Cognitive Science and its Applications forHuman-Computer Interaction Hillsdale,NJ: Lawrence Erlbaum Associates; 1988, 201-233.
26. Robertson GG, Mackinlay JD, Card SK. Cone trees: Animated 3D visualizations of hierarchical information. In Proceedings of CHI '91, New Orleans, LA, 1991, 189-194.
27. Eick SG, Wills GJ. Navigating large networks with hierarchies. In Proceedings of the IEEE Conference on Visualization, Los Alamitos, CA, 1993.
28. Wills GJ. NicheWorks: Interactive visualization of very large graphs Retrieved 4th August, 1998, from http://www.bell-labs.com/user/gwills/ NICHEguide/nichepaper.html
29. Chuah MC, Roth SF, Kolojejchick J, Mattis J, Juarez O. SageBook: Searching data-graphics by content. In Proceedings of CHI '95, Denver, CO, 1995, 338-345.
30. Kohonen T. Self-Organizing Maps: Springer; 1995.
31. Lamping J, Rao R, Pirolli P. A focus+context technique based on hyperbolic geometry for visualizing large hierarchies. In Proceedings of ACM CHI'95 Conference on Human Factors in Computing Systems, 1995, 401-408.
32. Munzner T. H3: Laying out large directed graphs in 3D hyperbolic space. In: Dill J, Gershon N, eds. Proceedings of the 1997 IEEE Symposium on Information Visualization. Phoenix: IEEE CS Press 1997, 2-10.
33. Card S, Mackinlay J, Shneiderman B, eds. Readings in Information Visualization: Using Vision to Think. San Francisco, CA: Morgan Kaufmann; 1999.
34. Chen C. Information Visualisation and Virtual Environments. London: Springer; 1999.
35. Spence B. Information Visualization. New York: Addison-Wesley; 2000.
36. Ware C. Information Visualization: Perception for Design. San Francisco: Morgan Kaufmann Publishers; 2000.
37. Thomas J, Cook K. Illuminating the Path, the Research and Development Agenda for Visual Analytics. Phoenix: IEEE CS Press; 2005.
38. Chen C, Paul RJ. Visualizing a knowledge domain's intellectual structure. Computer 2001, 34:65-71.
39. Bollen J, Sompel HVd, Hagberg A, Bettencourt L, Chute R, Rodriguez MA, Balakireval L. Clickstream data yields high-resolution maps of science. PLoS ONE 2009, 4:e4803.
40. Eccles R, Kapler T, Harper R, Wright W. Stories in GeoTime. Inf Vis 2008, 7:3-17.
41. MacEachren AM. How Maps Work: Representation, Visualization, and Design. New York: Guilford Press; 1995.
42. Chalmers M. Bead-an information visualization system. Proc Asis Annu Meet 1995, 32:249-249
43. Jerding DF, Stasko JT. The information mural: a technique for displaying and navigating large information spaces. IEEE Trans Vis Comput Graph 1998, 4:257-271.
44. Shneiderman B. The eyes have it: A task by data type taxonomy for information visualization. In Proceedings of IEEE Workshop on Visual Language, Boulder, CO, 1996, 336-343.
45. Lehrer J. The Eureka Hunt: why do good ideas come to us when they do? The New Yorker, July 28, 2008, 40-45.
46. Sternberg RJ, Davidson JE, eds. The Nature of Insight. MIT Press; 1996.
47. Chen C, Chen Y, Horowitz M, Hou H, Liu Z et al. Towards an explanatory and computational theory of scientific discovery. J Informetrics 2009, 3:191-209.
48. Plaisant C, Fekete JD, Grinstein G. Promoting insightbased evaluation of visualizations: from contest to benchmark repository. IEEE Trans Vis Comput Graph 2008, 14:120-134.
49. Lam H. A framework of interaction costs in information visualization. IEEE Trans Vis Comput Graph 2008, 14:1149-1156.
50. Norman, DA. The Design of Everyday Things. New York: Basic Books; 2002.
51. Chen C, Yu Y. Empirical studies of information visualization: a meta-analysis. Int J Hum Comput Stud 2000, 53:851-866.
52. Julien CA, Leide JE, Bouthillier F. Controlled user evaluations of information visualization interfaces for text retrieval: Literature review and meta-analysis. J AmSoc Inform Sci Technol 2008, 59:1012-1024.
53. Kerren A, Stasko JT, Fekete J-D, North C. Workshop report: information visualization-humancentered issues in visual representation, interaction, and evaluation. Inf Vis 2007, 6:189-196.
54. Liu ZC, Nersessian NJ, Stasko JT. Distributed Cognition as a Theoretical Framework for Information Visualization. IEEE Trans Vis Comput Graph 2008, 14:1173-1180.
55. Eick SG. Information visualization at 10. IEEE Comput Graph Appl 2005, 25:12-14.
56. Gray AG, Moore AW. N-body problems in statistical learning. Adv Neural Inf Process Syst 2001, 13:521-527.
57. Moore A. Very fast EM-based mixture model clustering using multiresolution kd-trees. In: Kearns M, Cohn D, eds. Advances in Neural Information Processing Systems: Morgan Kaufman; 1999, 543-549.
58. Holten D. Hierarchical edge bundles: visualization of adjacency relations in hierarchical data. IEEE Trans Vis Comput Graph 2006, 12:741-748.
59. Cui W, Zhou H, Qu H, Wong PC, Li X. Geometrybased edge clustering for graph visualization. IEEE Trans Vis Comput Graph 2008, 14:1277-1284.
60. Dwyer T, Koren Y, Marriott K. IPSep-CoLa: An Incremental Procedure for Separation Constraint Layout of Graphs. IEEE Trans Vis Comput Graph 2006, 12:821-828.
61. Bottger J, Balzer M, Deussen O. Complex logarithmic views for small details in large contexts. IEEE Trans Vis Comput Graph 2006, 12:845-852.
62. Luboschik M, Schumann H, Cords H. Particle-based labeling: fast point-feature labeling without obscuring other visual features. IEEE Trans Vis Comput Graph 2008, 14:1237-1244.
63. Chen C. Tracking latent domain structures: an integration of pathfinder and latent semantic analysis. AIDS Soc 1997, 11:48-62.
64. Chen C,Morris S. Visualizing evolving networks: Minimum spanning trees versus Pathfinder networks. In Proceedings of IEEE Symposium on Information Visualization, Seattle, Washington, 2003, 67-74.
65. Quirin A, Cordon O, Santamaria J, Vargas-Quesada B, Moya-Anegon F. A new variant of the Pathfinder algorithm to generate large visual science maps in cubic time. Inform Process Manage 2008, 44:1611-1623.
66. Schvaneveldt RW, ed. Pathfinder Associative Networks: Studies in Knowledge Organization. Norwood, NJ: Ablex Publishing Corporations; 1990.
67. Healey CG, Kocherlakota S, Rao V, Mehta R, Amant RS. Visual perception and mixed-initiative interaction for assisted visualization design. IEEE Trans Vis Comput Graph 2008, 14:396-411.
68. Chen H, Nunamaker J Jr, Titkova O. Information visualization for collaborative computing. Computer 1998, 31:75-82.
69. Isenberg P, Carpendale S. Interactive tree comparison for co-located collaborative information visualization. IEEE Trans Vis Comput Graph 2007, 13:1232-1239.
70. Wattenberg M, Kriss J. Designing for social data analysis. IEEE Trans Vis Comput Graph 2006, 12:549-557.
71. Kostelnick C. The visual rhetoric of data displays: the conundrum of clarity. IEEE Trans Professional Commun 2008, 51:116-130.
72. Rhyne T-M, Hibbard B, Johnson C, Chen C, Eick S. Can we determine the top unresolved problems of visualization? In Proceedings of IEEE Visualization 2004, Austin, Texas, 2004, 563-566.
73. Chen C. Top 10 unsolved information visualization problems. IEEE Comput Graph Appl 2005, 25:12-16.
74. Johnson CR, Moorhead R, Munzner T, Pfister H, Rheingans P et al., eds. NIH-NSF Visualization Research Challenges Report: IEEE Press; 2006.
75. Munzner T, Johnson C, Moorhead R, Pfister H, Rheingans P, Yoo T. NIH-NSF visualization research agenda report summary. IEEE Comput Graph Appl 2006, 26:20-24.
76. Burkhard RA, Andrienko G, Andrienko N, Dykes J, Koutamanis A et al. Visualization summit 2007: ten research goals for 2010. Inf Vis 2007, 6:169-188.
77. Clauset A, Newman MEJ, Moore C. Finding community structure in very large networks. Phys Rev E 2004, 70:066111.
78. Berry MW, Browne M, Langville AN, Pauca VP, Plemmons RJ. Algorithms and applications for approximate nonnegative matrix factorization. Comput Stat Data Anal 2007, 52:155-173.
79. Lee DD, Seung HS. Learning the parts of objects by nonnegative matrix factorization. Nature 1999, 401:788-791.
80. Dunbar K. Concept discovery in a scientific domain. Cogn Sci 1993, 17:397-434.
81. Soofi ES, Retzer JJ. Information indices: unification and applications. J Econom 2002, 107:17-40.
82. Bartels L. Issue voting under uncertainty: an empirical test. Am J Pol Sci 1988, 30:709-728.
83. Itti L, Baldi P. A Principled Approach to Detecting Surprising Events in Video. Proceedings of IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2005, 631-637.