Aritra Dasgupta and Min Chen and Robert Kosara.
Conceptualizing Visual Uncertainty in Parallel Coordinates.
In Computer Graphics Forum, vol. 31, no. 3, pp. 1015--1024, 2012.

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Abstract:

Uncertainty is an intrinsic part of any visual representation in visualization, no matter how precise the input data. Existing research on uncertainty in visualization mainly focuses on depicting data-space uncertainty in a visual form. Uncertainty is thus often seen as a problem to deal with, in the data, and something to be avoided if possible. In this paper, we highlight the need for analyzing visual uncertainty in order to design more effective visual representations. We study various forms of uncertainty in the visual representation of parallel coordinates and propose a taxonomy for categorizing them. By building a taxonomy, we aim to identify different sources of uncertainty in the screen space and relate them to different effects of uncertainty upon the user. We examine the literature on parallel coordinates and apply our taxonomy to categorize various techniques for reducing uncertainty. In addition, we consider uncertainty from a different perspective by identifying cases where increasing certain forms of uncertainty may even be useful, with respect to task, data type and analysis scenario. This work suggests that uncertainty is a feature that can be both useful and problematic in visualization, and it is beneficial to augment an information visualization pipeline with a facility for visual uncertainty analysis.

Bibtex:

@Article{        dasgupta:2012:CVUP,
  author = 	 {Aritra Dasgupta and Min Chen and Robert Kosara},
  title = 	 {Conceptualizing Visual Uncertainty in Parallel Coordinates},
  journal = 	 {Computer Graphics Forum},
  year = 	 {2012},
  volume = 	 {31},
  number = 	 {3},
  pages = 	 {1015--1024},
  month = 	 {June},
}

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References:

[AA01] ANDRIENKO G., ANDRIENKO N.: Constructing parallel coordinates plot for problem solving. In Proceedings Smart Graphics (2001), pp. 9-14. 6, 8
[AA04] ANDRIENKO G., ANDRIENKO N.: Parallel coordinates for exploring properties of subsets. Proceedings Coordinated and Multiple Views in Exploratory Visualization (2004), 93-104. 7
[AdOL04] ARTERO A. O., DE OLIVEIRA M. C. F., LEVKOWITZ H.: Uncovering clusters in crowded parallel coordinates visual- izations. Proceedings Information Visualization (2004), 81-88. 6, 7
[AES04] AMAR R., EAGAN J., STASKO J.: Low-level compo- nents of analytic activity in information visualization. Proceed- ings Information Visualization (2004), 111-117. 6
[BS06] BERTINI E., SANTUCCI G.: Visual quality metrics. In In Proceedings,BELIV Workshop (2006), pp. 1-5. 2
[BTK11] BERTINI E., TATU A., KEIM D.: Quality metrics in high-dimensional data visualization: an overview and systemati- zation. IEEE Tansactions on Visualization and Computer Graph- ics 17, 12 (2011), 2203-2212. 2, 9
1024 Dasgupta, Chen, Kosara / Conceptualizing Visual Uncertainty in Parallel Coordinates
[CCM09] CORREA C., CHAN Y., MA K.: A framework for uncertainty-aware visual analytics. In Visual Analytics Science and Technology, 2009. (2009), IEEE, pp. 51-58. 9
[Chi00] CHI E.: A taxonomy of visualization techniques using the data state reference model. In Proceedings Information Visu- alization (2000), pp. 69-75. 3
[CJ10] CHEN M., JA NICKE H.: An information-theoretic framework for visualization. Transactions on Visualization and Com- puter Graphics 16, 6 (2010), 1206-1215. 4
[CWRY06] CUI Q., WARD M., RUNDENSTEINER E., YANG J.: Measuring data abstraction quality in multiresolution visualiza- tions. Transactions on Visualization and Computer Graphics 12, 5 (2006), 709-716. 7
[DK10] DASGUPTA A., KOSARA R.: Pargnostics: Screen-space metrics for parallel coordinates. Transactions on Visualization and Computer Graphics 16, 6 (2010), 1017-26. 7, 8, 9
[DK11] DASGUPTA A., KOSARA R.: Adaptive privacy- preservation using parallel coordinates. Transactions on Visu- alization and Computer Graphics 17, 12 (2011), 2241-2248. 2, 4, 8, 9
[EBD05] ELLIS G., BERTINI E., DIX A.: The sampling lens: making sense of saturated visualisations. In CHI'05 Extended Abstracts on Human factors in Computing Systems (2005), pp. 1351-1354. 6
[ED06] ELLIS G., DIX A.: Enabling automatic clutter reduction in parallel coordinate plots. Transactions on Visualization and Computer Graphics 12, 5 (2006), 717-724. 7
[FWR99] FUA Y.-H., WARD M. O., RUNDENSTEINER E. A.: Hierarchical parallel coordinates for exploration of large datasets. In Proceedings, Visualization (1999), pp. 43-50. 7
[HHE08] HUANG W., HONG S.-H., EADES P.: Effects of Cross- ing Angles. In Proceedings Pacific Visualization Symposium (2008), pp. 41-46. 5
[HLS*12] HOLZHU TER C., LEX A., SCHMALSTIEG D., SCHULZ H.-J., SCHUMANN H., STREIT M.: Visualizing uncer- tainty in biological expression data. In Proceedings Visualization and Data Analysis (2012). 3
[Hub10] HUBBARD D.: How to measure anything: Finding the value of intangibles in business. Wiley, 2010. 3
[HVW10] HOLTEN D., VAN WIJK J.: Evaluation of cluster identification performance for different pcp variants. Computer Graphics Forum 29, 3 (2010), 793-802. 8
[ID90] INSELBERG A., DIMSDALE B.: Parallel coordinates: A tool for visualizing multi-dimensional geometry. In Proceedings Visualization (1990), pp. 361-378. 1
[JC08] JOHANSSON J., COOPER M.: A screen space quality method for data abstraction. Computer Graphics Forum 27, 3 (2008), 1039-1046. 6
[JS03] JOHNSON C., SANDERSON A.: A next step: Visualizing errors and uncertainty. Computer Graphics and Applications 23, 5 (2003), 6-10. 1
[KW99] KLIR G., WIERMAN M.: Uncertainty-based informa- tion: Elements of generalized information theory. Springer Ver- lag, 1999. 2
[LB98] LOPES A., BRODLIE K.: Accuracy in 3d particle trac- ing. Mathematical Visualization: Algorithms, Applications and Numerics (1998), 329-341. 1
[LPSW96] LODHA S., PANG A., SHEEHAN R., WITTENBRINK C.: Uflow: Visualizing uncertainty in fluid flow. In Proceedings Visualization (1996), pp. 249-254. 1
[Mil87] MILLIKEN F.: Three types of perceived uncertainty about the environment: State, effect, and response uncertainty. Academy of Management review (1987), 133-143. 2, 6
[NH06] NOVOTNY M., HAUSER H.: Outlier-preserving fo- cus+context visualization in parallel coordinates. Transactions on Visualization and Computer Graphics 12, 5 (2006), 893-900. 4, 7
[PAJKW08] PURCHASE H., ANDRIENKO N., JANKUN-KELLY T., WARD M.: Theoretical foundations of information visualiza- tion. In Information Visualization: Human-Centered Issues and Perspectives. Springer, 2008, pp. 46-64. 3, 8
[PWL97] PANG A., WITTENBRINK C., LODHA S.: Approaches to uncertainty visualization. The Visual Computer 13, 8 (1997), 370-390. 1, 2
[PWR04] PENG W., WARD M., RUNDENSTEINER E.: Clutter re- duction in multi-dimensional data visualization using dimension reordering. In Proceedings Information Visualization (2004), pp. 89-96. 6
[RLBS03] RHODES P., LARAMEE R., BERGERON R., SPARR T.: Uncertainty visualization methods in isosurface rendering. In Eurographics (2003), pp. 83-88. 1
[RNC*95] RUSSELL S., NORVIG P., CANNY J., MALIK J., ED- WARDS D.: Artificial intelligence: a modern approach. Prentice hall, 1995. 2, 3
[Sha48] SHANNON C. E.: A mathematical theory of communi- cation. The Bell System Technical Journal 27 (1948), 379-423. 3
[SLSR09] SKEELS M., LEE B., SMITH G., ROBERTSON G.: Re- vealing uncertainty for information visualization. Information Visualization 9, 1 (2009), 70-81. 2
[TA*09] TATU A., ALBUQUERQUE G., ET AL.: Combining auto- mated analysis and visualization techniques for effective explo- ration of high-dimensional data. In Proceedings Visual Analytics Science and Technology (2009), pp. 59-66. 2
[THM*05] THOMSON J., HETZLER E., MACEACHREN A., GA- HEGAN M., PAVEL M.: A typology for visualizing uncertainty. In Proceedings SPIE (2005), vol. 5669, pp. 146-157. 2
[TM04] TORY M., MO LLER T.: Rethinking visualization: A high-level taxonomy. Symposium on Information Visualization (2004), 151-158. 2
[War04] WARE C.: Information visualization: perception for de- sign. Morgan Kaufmann, 2004. 2
[Weg90] WEGMAN E.: Hyperdimensional data analysis using parallel coordinates. Journal of the American Statistical Asso- ciation 85 (1990), 664-675. 4
[WL97] WEGMAN E., LUO Q.: High dimensional clustering us- ing parallel coordinates and the grand tour. Computing Science and Statistics 28 (1997), 361-368. 8
[WPL96] WITTENBRINK C., PANG A., LODHA S.: Glyphs for visualizing uncertainty in vector fields. Transactions on Visual- ization and Computer Graphics 2, 3 (1996), 266-279. 1
[ZCQ*09] ZHOU H., CUI W., QU H., WU Y., YUAN X., ZHUO W.: Splatting the Lines in Parallel Coordinates. Computer Graphics Forum 28, 3 (2009), 759-766. 8
[ZK10] ZIEMKIEWICZ C., KOSARA R.: Embedding Information Visualization Within Visual Representation. Advances in Infor- mation and Intelligent Systems (2010), 307-326. 8
[ZYQ*08] ZHOU H., YUAN X., QU H., CUI W., CHEN B.: Visual clustering in parallel coordinates. Computer Graphics Fo- rum 27, 3 (2008), 1047-1054. 7