Visualizing High-Dimensional Data: Advances in the Past Decade

Eurographics Conference on Visualization - State of the Art Reports, EuroVis-STAR 2015

Volumn , Issue , 2015, Pages 127-147

  Liu, S ^a   Maljovec, D ^a   Wang, B ^a   Bremer, P T ^b   Pascucci, V ^a  

^a UNIVERSITY OF UTAH   (United States)

^b LAWRENCE LIVERMORE NATIONAL LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS; DATA VISUALIZATION; INFORMATION ANALYSIS; INFORMATION SYSTEMS;

COMPUTING RESOURCE; HIGH DIMENSIONAL DATA; HIGH DIMENSIONAL DATA VISUALIZATION; HIGH-DIMENSIONAL DATASET; MODULARS; SENSING DEVICES; VISUALIZATION RESEARCH;

VISUALIZATION;

EID: 84992368550     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.2312/eurovisstar.20151115     Document Type: Conference Paper

References (199)

1. ARTERO A., DE OLIVEIRA M., LEVKOWITZ H.: Uncovering clusters in crowded parallel coordinates visualizations. In IEEE Symposium on Information Visualization (2004), pp. 81-88. 11
2. ALBUQUERQUE G., EISEMANN M., LEHMANN D. J., THEISEL H., MAGNOR M.: Improving the visual analysis of high-dimensional datasets using quality measures. In IEEE Symposium on Visual Analytics Science and Technology (2010), IEEE, pp. 19-26. 8
3. ANKERST M., KEIM D. A., PETER KRIEGEL H.: Circle segments: A technique for visually exploring large multidimensional data sets. In Proceedings of IEEE Visualization, Hot Topic Session. (1996). 9
4. ANAND A., WILKINSON L., DANG T. N.: Visual pattern discovery using random projections. In IEEE Conference on Visual Analytics Science and Technology (2012), IEEE, pp. 43-52. 5, 11
5. BUJA A., COOK D., SWAYNE D. F.: Interactive high-dimensional data visualization. Journal of Computational and Graphical Statistics 5, 1 (1996), pp. 78-99. 1
6. BIASOTTI S., DE FLORIANI L., FALCIDIENO B., FROSINI P., GIORGI D., LANDI C., PAPALEO L., SPAGNUOLO M.: Describing shapes by geometrical-topological properties of real functions. ACM Computing Surveys 40, 4 (2008), 12:1-12:87. 6
7. BISWAS A., DUTTA S., SHEN H.-W., WOODRING J.: An information-aware framework for exploring multivariate data sets. IEEE Transactions on Visualization and Computer Graphics 19, 12 (2013), 2683-2692. 3
8. BECK F.: Survis. https://github.com/fabian-beck/survis, 2014. 2
9. BREMER P.-T., EDELSBRUNNER H., HAMANN B., PASCUCCI V.: A topological hierarchy for functions on triangulated surfaces. IEEE Transactions on Visualization and Computer Graphics 10, 385-396 (2004). 6
10. BÜRGER R., HAUSER H.: Visualization of multi-variate scientific data. EuroGraphics State of the Art Reports (STARs) (2007), 117-134. 1, 3, 12
11. BENDIX F., KOSARA R., HAUSER H.: Parallel sets: visual analysis of categorical data. In IEEE Symposium on Information Visualization (2005), pp. 133-140. 3
12. BROWN E. T., LIU J., BRODLEY C. E., CHANG R.: Dis-function: Learning distance functions interactively. In IEEE Conference on Visual Analytics Science and Technology (2012), IEEE, pp. 83-92. 4, 12, 14
13. BEKETAYEV K., MOROZOV D., WEBER G. H., ABZHANOV A., HAMANN. B.: Geometry-preserving topological landscapes. In Proceedings of the Workshop at SIGGRAPH Asia (2012), pp. 155-160. 9
14. BELKIN M., NIYOGI P.: Laplacian eigenmaps for dimensionality reduction and data representation. Neural computation 15, 6 (2003), 1373-1396. 4
15. BERGER W., PIRINGER H., FILZMOSER P., GRÖLLER E.: Uncertainty-aware exploration of continuous parameter spaces using multivariate prediction. Computer Graphics Forum 30, 3 (2011), 911-920. 5, 11
16. BAUMGARTNER C., PLANT C., RAILING K., KRIEGEL H.-P., KROGER P.: Subspace selection for clustering high-dimensional data. In Fourth IEEE International Conference on Data Mining (2004), IEEE, pp. 11-18. 5, 13
17. BERTINI E., TATU A., KEIM D.: Quality metrics in high-dimensional data visualization: an overview and systematization. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 2203-2212. 1, 2, 10
18. BACHTHALER S., WEISKOPF D.: Continuous scatterplots. IEEE Transactions on Visualization and Computer Graphics 14, 6 (2008), 1428-1435. 10, 12
19. BACHTHALER S., WEISKOPF D.: Efficient and adaptive rendering of 2-d continuous scatterplots. Computer Graphics Forum 28, 3 (2009), 743-750. 10
20. CARLSSON G.: Topology and data. Bullentin of the American Mathematical Society 46, 2 (2009), 255-308. 2, 6
21. CORREA C., CHAN Y.-H., MA K.-L.: A framework for uncertainty-aware visual analytics. In IEEE Symposium on Visual Analytics Science and Technology (2009), pp. 51-58. 8, 14
22. CHAN Y.-H., CORREA C., MA K.-L.: Flow-based scatterplots for sensitivity analysis. In IEEE Symposium on Visual Analytics Science and Technology (2010), IEEE, pp. 43-50. 8
23. CHAN Y.-H., CORREA C., MA K.-L.: The generalized sensitivity scatterplot. IEEE Transactions on Visualization and Computer Graphics 19, 10 (2013), 1768-1781. 8
24. CARR H., DUKE D.: Joint contour nets. IEEE Transactions on Visualization and Computer Graphics 20, 8 (2014), 1100-1113. 6
25. CHENG C.-H., FU A. W., ZHANG Y.: Entropy-based subspace clustering for mining numerical data. In Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining (1999), ACM, pp. 84-93. 5, 11, 13
26. CAO N., GOTZ D., SUN J., QU H.: Dicon: Interactive visual analysis of multidimensional clusters. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 2581-2590. 8
27. CHAN W. W.-Y.: A survey on multivariate data visualization. Department of Computer Science and Engineering. Hong Kong University of Science and Technology 8, 6 (2006), 1-29. 1
28. CHERNOFF H.: The use of faces to represent points in k-dimensional space graphically. Journal of the American Statistical Association 68, 342 (1973), 361-368. 8
29. CORREA C., LINDSTROM P.: Towards robust topology of sparsely sampled data. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 1852-1861. 6, 14
30. CAAT M., MAURITS N., ROERDINK J.: Design and evaluation of tiled parallel coordinates visualization of multichannel eeg data. IEEE Transactions on Visualization and Computer Graphics 13, 1 (2007), 70-79. 8
31. CARD S. K., MACKINLAY J. D., SHNEIDERMAN B.: Readings in information visualization: using vision to think. Morgan Kaufmann, 1999. 1, 2
32. CARR H., SNOEYINK J., AXEN U.: Computing contour trees in all dimensions. Computational Geometry 24, 2 (2003), 75 - 94. Special Issue on the Fourth CGC Workshop on Computational Geometry. 6
33. CLAESSEN J., VAN WIJK J.: Flexible linked axes for multivariate data visualization. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 2310-2316. 8
34. DANG T. N., ANAND A., WILKINSON L.: Timeseer: Scagnostics for high-dimensional time series. IEEE Transactions on Visualization and Computer Graphics 19, 3 (2013), 470-483. 7
35. DEMIR D., BEKETAYEV K., WEBER G. H., BREMER P.-T., PASCUCCI V., HAMANN. B.: Topology exploration with hierarchical landscapes. In Proceedings of the Workshop at SIGGRAPH Asia (2012), pp. 147-154. 9, 13
36. DUKE D., CARR H., KNOLL A., SCHUNCK N., NAM H. A., STASZCZAK A.: Visualizing nuclear scission through a multifield extension of topological analysis. IEEE Transactions on Visualization and Computer Graphics 18, 12 (2012), 2033-2040. 6, 14
37. DASGUPTA A., KOSARA R.: Pargnostics: Screen-space metrics for parallel coordinates. IEEE Transactions on Visualization and Computer Graphics 16, 6 (2010), 1017-1026. 11
38. DJURCILOV S., KIM K., LERMUSIAUX P., PANG A.: Visualizing scalar volumetric data with uncertainty. Computers and Graphics 26 (2002), 239-248. 14
39. DE OLIVEIRA M. C. F., LEVKOWITZ H.: From visual data exploration to visual data mining: A survey. IEEE Transactions on Visualization and Computer Graphics 9, 3 (2003), 378-394. 1, 11
40. DONOHO D. L.: High-dimensional data analysis: The curses and blessings of dimensionality. AMS Lecture: Math Challenges of the 21st Century, 2000. 13
41. DE SILVA V., MOROZOV D., VEJDEMOJOHANSSON M.: Persistent cohomology and circular coordinates. In Proceedings 25th Annual Symposium on Computational Geometry (2009), pp. 227-236. 6
42. DE SILVA V., TENENBAUM J. B.: Sparse multidimensional scaling using landmark points. Tech. rep., Technical report, Stanford University, 2004. 4, 12
43. DEMIR I., WESTERMANN R.: Progressive high-quality response surfaces for visually guided sensitivity analysis. Computer Graphics Forum 32, 3pt1 (2013), 21-30. 5
44. DANG T. N., WILKINSON L., ANAND A.: Stacking graphic elements to avoid over-plotting. IEEE Transactions on Visualization and Computer Graphics 16, 6 (2010), 1044-1052. 7
45. ELLIS G., DIX A.: A taxonomy of clutter reduction for information visualisation. IEEE Transactions on Visualization and Computer Graphics 13, 6 (2007), 1216-1223. 1
46. ELMQVIST N., DRAGICEVIC P., FEKETE J.-D.: Rolling the dice: Multidimensional visual exploration using scatterplot matrix navigation. IEEE Transactions on Visualization and Computer Graphics 14, 6 (2008), 1539-1148. 10
47. EDELSBRUNNER H., HARER J.: Persistent homology - a survey. Contemporary Mathematics 453 (2008), 257. 6
48. EDELSBRUNNER H., HARER J.: Computational Topology - an Introduction. American Mathematical Society, 2010. 6
49. EDELSBRUNNER H., HARER J., NATARAJAN V., PASCUCCI V.: Morse-Smale complexes for piece-wise linear 3-manifolds. In Proceedings 19th Annual symposium on Computational geometry (2003), pp. 361-370. 6
50. EDELSBRUNNER H., HARER J., ZOMORODIAN A. J.: Hierarchical Morse-Smale complexes for piecewise linear 2-manifolds. Discrete and Computational Geometry 30, 87-107 (2003). 6
51. ENGEL D., ROSENBAUM R., HAMANN B., HAGEN H.: Structural decomposition trees. Computer Graphics Forum 30, 3 (2011), 921-930. 9
52. ELMQVIST N., STASKO J., TSIGAS P.: Datameadow: A visual canvas for analysis of large-scale multivariate data. In IEEE Symposium on Visual Analytics Science and Technology (2007), pp. 187-194. 8
53. FERDOSI B. J., BUDDELMEIJER H., TRAGER S., WILKINSON M. H., ROERDINK J. B.: Finding and visualizing relevant subspaces for clustering high-dimensional astronomical data using connected morphological operators. In IEEE Symposium on Visual Analytics Science and Technology (2010), IEEE, pp. 35-42. 5, 7, 11, 13
54. FANEA E., CARPENDALE S., ISENBERG T.: An interactive 3d integration of parallel coordinates and star glyphs. In IEEE Symposium on Information Visualization (2005), pp. 149-156. 8
55. FERDOSI B. J., ROERDINK J. B.: Visualizing high-dimensional structures by dimension ordering and filtering using subspace analysis. Computer Graphics Forum 30, 3 (2011), 1121-1130. 7
56. FRIEDMAN J., TUKEY J.: A projection pursuit algorithm for exploratory data analysis. IEEE Transactions on Computers C-23, 9 (1974), 881-890. 5, 13
57. FUA Y.-H., WARD M., RUNDENSTEINER E.: Structure-based brushes: a mechanism for navigating hierarchically organized data and information spaces. IEEE Transactions on Visualization and Computer Graphics 6, 2 (2000), 150-159. 9
58. GYULASSY A., BREMER P.-T., PASCUCCI V., HAMANN B.: A practical approach to Morse-Smale complex computation: Scalability and generality. IEEE Transactions on Visualization and Computer Graphics 14, 6 (2008), 1619-1626. 6
59. GERBER S., BREMER P., PASCUCCI V., WHITAKER R.: Visual exploration of high dimensional scalar functions. IEEE Transactions on Visualization and Computer Graphics 16, 6 (2010), 1271-1280. 3, 5, 6, 13, 14
60. GRATZL S., GEHLENBORG N., LEX A., PFISTER H., STREIT M.: Domino: Extracting, comparing, and manipulating subsets across multiple tabular datasets. IEEE Transactions on Visualization and Computer Graphics 20, 12 (2014), 2023-2032. 12
61. GHRIST R.: Barcodes: The persistent topology of data. Bulletin of the American Mathematical Society 45 (2008), 61-75. 6
62. GLEICHER M.: Explainers: Expert explorations with crafted projections. IEEE Transactions on Visualization and Computer Graphics 19, 12 (2013), 2042-2051. 4, 12, 14
63. GRATZL S., LEX A., GEHLENBORG N., PFISTER H., STREIT M.: Lineup: Visual analysis of multi-attribute rankings. IEEE Transactions on Visualization and Computer Graphics 19, 12 (2013), 2277-2286. 12
64. GYULASSY A., NATARAJAN V., PASCUCCI V., BREMER P.-T., HAMANN B.: Topology-based simplification for feature extraction from 3D scalar fields. In Proceedings of IEEE Visualization (2005), pp. 535-542. 6
65. GENG Z., PENG Z., LARAMEE R., ROBERTS J., WALKER R.: Angular histograms: Frequency-based visualizations for large, high dimensional data. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 2572-2580. 8
66. GUO D.: Coordinating computational and visual approaches for interactive feature selection and multivariate clustering. Information Visualization 2, 4 (2003), 232-246. 7
67. GUO Z., WARD M., RUNDENSTEINER E., RUIZ C.: Pointwise local pattern exploration for sensitivity analysis. In IEEE Conference on Visual Analytics Science and Technology (2011), pp. 131-140. 8
68. GUO P., XIAO H., WANG Z., YUAN X.: Interactive local clustering operations for high dimensional data in parallel coordinates. In IEEE Pacific Visualization Symposium (2010), pp. 97-104. 12
69. GUO H., XIAO H., YUAN X.: Scalable multivariate volume visualization and analysis based on dimension projection and parallel coordinates. IEEE transactions on visualization and computer graphics (2012). 13
70. HU X., BRADEL L., MAITI D., HOUSE L., NORTH C.: Semantics of directly manipulating spatializations. IEEE Transactions on Visualization and Computer Graphics 19, 12 (2013), 2052-2059. 12, 14
71. HAO M., DAYAL U., KEIM D., MORENT D., SCHNEIDEWIND J.: Intelligent visual analytics queries. In IEEE Symposium on Visual Analytics Science and Technology (2007), pp. 91-98. 11
72. HOFFMAN P. E., GRINSTEIN G. G.: A survey of visualizations for high-dimensional data mining. Information visualization in data mining and knowledge discovery (2002), 47-82. 1
73. HOFFMAN P., GRINSTEIN G., MARX K., GROSSE I., STANLEY E.: DNA visual and analytic data mining. In Proceedings of IEEE Visualization (1997), pp. 437-441. 7
74. HURLEY C., OLDFORD R.: Pairwise display of high-dimensional information via eulerian tours and hamiltonian decompositions. Journal of Computational and Graphical Statistics 19, 4 (2010). 7
75. HEER J., ROBERTSON G. G.: Animated transitions in statistical data graphics. IEEE Transactions on Visualization and Computer Graphics 13, 6 (2007), 1240-1247. 10
76. HASTIE T., STUETZLE W.: Principal curves. Journal of the American Statistical Association 84, 406 (1989), 502-516. 5
77. HAGH-SHENAS H., KIM S., INTERRANTE V., HEALEY C.: Weaving versus blending: a quantitative assessment of the information carrying capacities of two alternative methods for conveying multivariate data with color. IEEE Transactions on Visualization and Computer Graphics 13, 6 (2007), 1270-1277. 11
78. HURTER C., TELEA A., ERSOY O.: Moleview: An attribute and structure-based semantic lens for large element-based plots. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 2600-2609. 10, 12
79. HOLTEN D., VAN WIJK J. J.: Evaluation of cluster identification performance for different PCP variants. Computer Graphics Forum 29, 3 (2010), 793-802. 10
80. HEINRICH J., WEISKOPF D.: Continuous parallel coordinates. IEEE Transactions on Visualization and Computer Graphics 15, 6 (2009), 1531-1538. 10
81. HARVEY W., WANG Y.: Topological landscape ensembles for visualization of scalar-valued functions. Computer Graphics Forum 29, 3 (2010), 993-1002. 9, 13
82. HEINRICH J., WEISKOPF D.: State of the art of parallel coordinates. STAR Proceedings of Eurographics 2013 (2013), 95-116. 1
83. INSELBERG A., DIMSDALE B.: Parallel coordinates. In Human-Machine Interactive Systems. Springer, 1991, pp. 199-233. 7
84. IM J.-F., MCGUFFIN M., LEUNG R.: Gplom: The generalized plot matrix for visualizing multidimensional multivariate data. IEEE Transactions on Visualization and Computer Graphics 19, 12 (2013), 2606-2614. 3
85. INSELBERG A.: Parallel Coordinates: Visual Multidimensional Geometry and its Applications. Springer, 2009. 1, 7
86. JOHANSSON J., COOPER M.: A screen space quality method for data abstraction. Computer Graphics Forum 27, 3 (2008), 1039-1046. 11, 12
87. JOHANSSON S., JOHANSSON J.: Interactive dimensionality reduction through user-defined combinations of quality metrics. IEEETransactionsonVisualizationandComputerGraphics 15, 6 (2009), 993-1000. 7
88. JOHANSSON J., LJUNG P., JERN M., COOPER M.: Revealing structure within clustered parallel coordinates displays. In IEEE Symposium on Information Visualization (2005), IEEE, pp. 125-132. 10, 12
89. JAYARAMAN S., NORTH C.: A radial focus+context visualization for multi-dimensional functions. In Proceedings of IEEE Visualization (2002), pp. 443-450. 8
90. JOHNSON C. R.: Top scientific visualization research problems. IEEE Computer Graphics and Applications (2004). 14
91. JOLLIFFE I.: Principal component analysis. Wiley Online Library, 2005. 3
92. JOIA P., PAULOVICH F., COIMBRA D., CUMINATO J., NONATO L.: Local affine multidimensional projection. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 2563-2571. 4, 12
93. JEONG D. H., ZIEMKIEWICZ C., FISHER B., RIBARSKY W., CHANG R.: iPCA: An interactive system for pcabased visual analytics. Computer Graphics Forum 28, 3 (2009), 767-774. 3
94. KANDOGAN E.: Star coordinates: A multi-dimensional visualization technique with uniform treatment of dimensions. In IEEE Information Visualization Symposium, Late Breaking Hot Topics (2000), pp. 9-12. 7
95. KOREN Y., CARMEL L.: Visualization of labeled data using linear transformations. In IEEE Symposium on Information Visualization (2003), pp. 121-128. 4, 11
96. KEIM D. A.: Information visualization and visual data mining. IEEE Transactions on Visualization and Computer Graphics 8, 1 (2002), 1-8. 1, 11
97. KUHNE L., GIESEN J., ZHANG Z., HA S., MUELLER K.: A data-driven approach to hue-preserving color-blending. IEEE Transactions on Visualization and Computer Graphics 18, 12 (2012), 2122-2129. 11
98. KEHRER J., HAUSER H.: Visualization and visual analysis of multifaceted scientific data: A survey. IEEE Transactions on Visualization and Computer Graphics 19, 3 (2013), 495-513. 1, 3, 12
99. KEIM D., HAO M., LADISCH J., HSU M., DAYAL U.: Pixel bar charts: a new technique for visualizing large multi-attribute data sets without aggregation. In IEEE Symposium on Information Visualization (2001), pp. 113-120. 9, 11
100. KEIM D., KRIEGEL H.-P.: Visdb: database exploration using multidimensional visualization. Computer Graphics and Applications, IEEE 14, 5 (1994), 40-49. 9
101. KEIM D. A., KRIEGEL H.-P.: Visualization techniques for mining large databases: A comparison. Knowledge and Data Engineering, IEEE Transactions on 8, 6 (1996), 923-938. 11
102. KEIM D., KRIEGEL H.-P., ANKERST M.: Recursive pattern: a technique for visualizing very large amounts of data. In Proceedings of IEEE Visualization (1995), pp. 279-286, 463. 9
103. KRUSKAL J. B.: Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika 29, 1 (1964), 1-27. 4
104. KREUSELER M., SCHUMANN H.: A flexible approach for visual data mining. IEEE Transactions on Visualization and Computer Graphics 8, 1 (2002), 39-51. 9
105. LEUNG Y. K., APPERLEY M. D.: A review and taxonomy of distortion-oriented presentation techniques. ACM Transactions on Computer-Human Interaction 1, 2 (1994), 126-160. 10, 12
106. LEHMANN D. J., ALBUQUERQUE G., EISEMANN M., MAGNOR M., THEISEL H.: Selecting coherent and relevant plots in large scatterplot matrices. Computer Graphics Forum 31, 6 (2012), 1895-1908. 7
107. LAWRENCE J., ARIETTA S., KAZHDAN M., LEPAGE D., O'HAGAN C.: A user-assisted approach to visualizing multidimensional images. IEEE Transactions on Visualization and Computer Graphics 17, 10 (2011), 1487-1498. 3
108. LEE J. H., MCDONNELL K. T., ZELENYUK A., IMRE D., MUELLER K.: A structure-based distance metric for high-dimensional space exploration with multidimensional scaling. IEEE Transations on Visualization and Computer Graphics 20, 3 (2014), 351-364. 4
109. LEE A. B., PEDERSEN K. S., MUMFORD D.: The nonlinear statistics of high-contrast patches in natural images. International Journal of Computer Vision 54, 1-3 (2003), 83-103. 6
110. LEHMANN D., THEISEL H.: Features in continuous parallel coordinates. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 1912-1921. 10
111. LEHMANN D. J., THEISEL H.: Orthographic star coordinates. IEEE Transactions on Visualization and Computer Graphics 19, 12 (2013), 2615-2624. 7
112. LEE J. A., VERLEYSEN M.: Quality assessment of dimensionality reduction: Rank-based criteria. Neurocomputing 72, 7 (2009), 1431-1443. 4
113. LIU S., WANG B., BREMER P.-T., PASCUCCI V.: Distortion-guided structure-driven interactive exploration of high-dimensional data. Computer Graphics Forum 33, 3 (2014), 101-110. 4, 12, 14
114. LIU S., WANG B., THIAGARAJAN J. J., BREMER P.-T., PASCUCCI V.: Multivariate volume visualization through dynamic projections. Large Data Analysis and Visualization (LDAV), 2014 IEEE Symposium on (2014). 13, 14
115. LIU S., WANG B., THIAGARAJAN J. J., BREMER P.-T., V V. P.: Visual exploration of high-dimensional data: Subspace analysis through dynamic projections. Tech. Rep. UUSCI-2014-003, SCI Institute, University of Utah, 2014. 14
116. MAYORGA A., GLEICHER M.: Splatterplots: Overcoming overdraw in scatter plots. IEEE Transactions on Visualization and Computer Graphics 19, 9 (2013), 1526-1538. 10, 13
117. MOKBEL B., LUEKS W., GISBRECHT A., HAMMER B.: Visualizing the quality of dimensionality reduction. Neurocomputing 112 (2013), 109-123. 4
118. MCDONNELL K. T., MUELLER K.: Illustrative parallel coordinates. Computer Graphics Forum 27, 3 (2008), 1031-1038. 10, 11
119. MUHLBACHER T., PIRINGER H., GRATZL S., SEDLMAIR M., STREIT M.: Opening the black box: Strategies for increased user involvement in existing algorithm implementations. IEEE Transactions on Visualization and Computer Graphics 20, 12 (2014), 1643-1652. 11
120. MORRISON A., ROSS G., CHALMERS M.: A hybrid layout algorithm for sub-quadratic multidimensional scaling. In IEEE Symposium on Information Visualization (2002), IEEE, pp. 152-158. 11
121. MUNZNER T.: Visualization Analysis and Design. CRC Press, 2014. 1, 2
122. MIGUT M., WORRING M.: Visual exploration of classification models for risk assessment. In IEEE Symposium on Visual Analytics Science and Technology (2010), pp. 11-18. 13
123. NOVOTNY M., HAUSER H.: Outlier-preserving focus+context visualization in parallel coordinates. IEEE Transactions on Visualization and Computer Graphics 12, 5 (2006), 893-900. 7
124. NICOLAU M., LEVINE A. J., CARLSSON G.: Topology based data analysis identifies a subgroup of breast cancers with a unique mutational profile and excellent survival. In Proceedings of the National Academy of Sciences (2011), vol. 108, pp. 7265-7270. 6
125. NAM J. E., MUELLER K.: Tripadvisor-nd: A tourism-inspired high-dimensional space exploration framework with overview and detail. IEEE Transactions on Visualization and Computer Graphics 19, 2 (2013), 291-305. 5, 10
126. OESTERLING P., HEINE C., JANICKE H., SCHEUERMANN G., HEYER G.: Visualization of high-dimensional point clouds using their density distribution's topology. IEEE Transactions on Visualization and Computer Graphics 17, 11 (2011), 1547-1559. 9
127. OESTERLING P., HEINE C., JÄNICKE H., SCHEUERMANN G.: Visual analysis of high dimensional point clouds using topological landscape. In IEEE Pacific Visualization Symposium (2010), pp. 113-120. 9
128. OESTERLING P., HEINE C., WEBER G., SCHEUERMANN G.: Visualizing nd point clouds as topological landscape profiles to guide local data analysis. IEEE Transactions on Visualization and Computer Graphics 19, 3 (2013), 514-526. 9
129. PIRINGER H., BERGER W., KRASSER J.: Hypermoval: Interactive visual validation of regression models for real-time simulation. In Proceedings of the 12th Eurographics/IEEE - VGTC Conference on Visualization (2010), EuroVis'10, Eurographics Association, pp. 983-992. 3, 5
130. PASCUCCI V., COLE-MCLAUGHLIN K., SCORZELLI G.: The toporrery: Computation and presentation of multiresolution topology. Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration (2009), 19-40. 9
131. PORTES DOS SANTOS AMORIM E., BRAZIL E. V., DANIELS J., JOIA P., NONATO L. G., SOUSA M. C.: ilamp: Exploring high-dimensional spacing through backward multidimensional projection. In IEEE Conference on Visual Analytics Science and Technology (2012), IEEE, pp. 53-62. 12, 14
132. PAULOVICH F., ELER D., POCO J., BOTHA C., MINGHIM R., NONATO L.: Piece wise laplacian-based projection for interactive data exploration and organization. Computer Graphics Forum 30, 3 (2011), 1091-1100. 4, 12
133. POCO J., ETEMADPOUR R., PAULOVICH F., LONG T., ROSENTHAL P., OLIVEIRA M., LINSEN L., MINGHIM R.: A framework for exploring multidimensional data with 3d projections. Computer Graphics Forum 30, 3 (2011), 1111-1120. 12
134. PAULOVICH F., NONATO L., MINGHIM R., LEVKOWITZ H.: Least square projection: A fast high-precision multidimensional projection technique and its application to document mapping. IEEE Transactions on Visualization and Computer Graphics 14, 3 (2008), 564-575. 4, 12
135. PASCUCCI V., SCORZELLI G., BREMER P.-T., MASCARENHAS A.: Robust on-line computation of reeb graphs: Simplicity and speed. ACM Transactions on Graphics 26, 3 (2007). 6
136. PAULOVICH F., SILVA C., NONATO L.: Two-phase mapping for projecting massive data sets. IEEE Transactions on Visualization and Computer Graphics 16, 6 (2010), 1281-1290. 4, 12
137. POTTER K., WILSON A., BREMER P.-T., WILLIAMS D., PASCUCCI V., JOHNSON C.: Ensemblevis: A flexible approach for the statistical visualization of ensemble data. In Proceedings of IEEE Workshop on Knowledge Discovery from Climate Data: Prediction, Extremes, and Impacts (2009). 14
138. PENG W., WARD M. O., RUNDENSTEINER E. A.: Clutter reduction in multi-dimensional data visualization using dimension reordering. In IEEE Symposium on Information Visualization (2004), IEEE, pp. 89-96. 7, 12
139. RAO R., CARD S. K.: The table lens: merging graphical and symbolic representations in an interactive focus+ context visualization for tabular information. In Proceedings of the SIGCHI conference on Human factors in computing systems (1994), ACM, pp. 318-322. 10
140. RHEINGANS P., DESJARDINS M.: Visualizing high-dimensional predictive model quality. In Proceedings of IEEE Visualization (2000), pp. 493-496. 13
141. REEB G.: Sur les points singuliers d'une forme de pfaff completement intergrable ou d'une fonction numerique [on the singular points of a complete integral pfaff form or of a numerical function]. Comptes Rendus Acad. Science Paris 222 (1946), 847-849. 6
142. REDDY C. K., POKHARKAR S., HO T. K.: Generating hypotheses of trends in high-dimensional data skeletons. In IEEE Symposium on Visual Analytics Science and Technology (2008), IEEE, pp. 139-146. 5
143. ROSARIO G. E., RUNDENSTEINER E. A., BROWN D. C., WARD M. O., HUANG S.: Mapping nominal values to numbers for effective visualization. Information Visualization 3, 2 (2004), 80-95. 3
144. ROWEIS S. T., SAUL L. K.: Nonlinear dimensionality reduction by locally linear embedding. Science 290, 5500 (2000), 2323-2326. 4, 11
145. RASMUSSEN C. E., WILLIAMS C. K. I.: Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning). The MIT Press, 2006. 5
146. ROSENBAUM R., ZHI J., HAMANN B.: Progressive parallel coordinates. In IEEE Pacific Visualization Symposium (2012), pp. 25-32. 7
147. SHNEIDERMAN B.: Tree visualization with tree-maps: 2-d space-filling approach. ACM Transactions on graphics (TOG) 11, 1 (1992), 92-99. 9
148. SWAYNE D. F., LANG D. T., BUJA A., COOK D.: GGobi: evolving from XGobi into an extensible framework for interactive data visualization. Computational Statistics & Data Analysis 43, 4 (2003), 423-444. 9, 12
149. SMALE S.: On gradient dynamical systems. The Annals of Mathematics 74 (1961), 199-206. 6
150. SINGH G., MEMOLI F., CARLSSON G.: Topological methods for the analysis of high dimensional data sets and 3d object recognition. In Symposium on Point Based Graphics (2007), pp. 91-100. 3, 6, 13
151. SEDLMAIR M., MUNZNER T., TORY M.: Empirical guidance on scatterplot and dimension reduction technique choices. IEEE Transactions on Visualization and Computer Graphics 19, 12 (2013), 2634-2643. 10
152. SIPS M., NEUBERT B., LEWIS J. P., HANRAHAN P.: Selecting good views of high-dimensional data using class consistency. Computer Graphics Forum 28, 3 (2009), 831-838. 7
153. SEO J., SHNEIDERMAN B.: A rank-by-feature framework for unsupervised multidimensional data exploration using low dimensional projections. In IEEE Symposium on Information Visualization (2004), IEEE, pp. 65-72. 7, 13
154. SMOLA A. J., SCHÖLKOPF B.: A tutorial on support vector regression. Statistics and Computing 14, 3 (2004), 199-222. 5
155. SEO J., SHNEIDERMAN B.: Knowledge discovery in high-dimensional data: Case studies and a user survey for the rank-by-feature framework. IEEE Transactions on Visualization and Computer Graphics 12, 3 (2006), 311-322. 7
156. SCHNEIDEWIND J., SIPS M., KEIM D. A.: Pixnostics: Towards measuring the value of visualization. In IEEE Symposium on Visual Analytics Science and Technology (2006), IEEE, pp. 199-206. 11
157. SEIFERT C., SABOL V., KIENREICH W.: Stress maps: analysing local phenomena in dimensionality reduction based visualisations. In IEEE International Symposium on Visual Analytics Science and Technology. (2010). 4
158. STOLTE C., TANG D., HANRAHAN P.: Polaris: a system for query, analysis, and visualization of multidimensional relational databases. IEEE Transactions on Visualization and Computer Graphics 8, 1 (2002), 52-65. 11
159. STOLTE C., TANG D., HANRAHAN P.: Multiscale visualization using data cubes. IEEE Transactions on Visualization and Computer Graphics 9, 2 (2003), 176-187. 11
160. SCHRECK T., VON LANDESBERGER T., BREMM S.: Techniques for precision-based visual analysis of projected data. Information Visualization 9, 3 (2010), 181-193. 4, 14
161. SHRINIVASAN Y. B., VAN WIJK J. J.: Supporting exploratory analysis with the select & slice table. Computer Graphics Forum 29, 3 (2010), 803-812. 12
162. SANFTMANN H., WEISKOPF D.: Illuminated 3d scatterplots. Computer Graphics Forum 28, 3 (2009), 751-758. 10, 12
163. SANFTMANN H., WEISKOPF D.: 3d scatterplot navigation. IEEE Transactions on Visualization and Computer Graphics 18, 11 (2012), 1969-1978. 12
164. SANYAL J., ZHANG S., DYER J., MERCER A., AM-BURN P., MOORHEAD R. J.: Noodles: A tool for visualization of numerical weather model ensemble uncertainty. IEEE Transactions on Visualization and Computer Graphics 16, 6 (2010), 1421 - 1430. 14
165. TATU A., ALBUQUERQUE G., EISEMANN M., SCHNEIDEWIND J., THEISEL H., MAGNOR M., KEIM D.: Combining automated analysis and visualization techniques for effective exploration of high-dimensional data. In IEEE Symposium on Visual Analytics Science and Technology (2009), IEEE, pp. 59-66. 7, 11, 13
166. TENENBAUM J. B., DE SILVA V., LANGFORD J. C.: A global geometric framework for nonlinear dimensionality reduction. Science 290, 5500 (2000), 2319-2323. 4
167. TAM G. K. L., FANG H., AUBREY A. J., GRANT P. W., ROSIN P. L., MARSHALL D., CHEN M.: Visualization of time-series data in parameter space for understanding facial dynamics. Computer Graphics Forum 30, 3 (2011), 901-910. 3
168. TURKAY C., FILZMOSER P., HAUSER H.: Brushing dimensions-a dual visual analysis model for high-dimensional data. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 2591-2599. 4, 11, 12
169. TAKAHASHI S., FUJISHIRO I., OKADA M.: Applying manifold learning to plotting approximate contour trees. IEEE Transactions on Visualization and Computer Graphics 15, 6 (2009), 1185-1192. 14
170. TURKAY C., JEANQUARTIER F., HOLZINGER A., HAUSER H.: On computationally-enhanced visual analysis of heterogeneous data and its application in biomedical informatics. In Interactive Knowledge Discovery and Data Mining in Biomedical Informatics. Springer, 2014, pp. 117-140. 11
171. TURKAY C., LUNDERVOLD A., LUNDERVOLD A. J., HAUSER H.: Representative factor generation for the interactive visual analysis of high-dimensional data. IEEE Transactions on Visualization and Computer Graphics 18, 12 (2012), 2621-2630. 4, 11
172. TEOH S. T., MA K.-L.: Paintingclass: interactive construction, visualization and exploration of decision trees. In Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining (2003), ACM, pp. 667-672. 13
173. TZENG F.-Y., MA K.-L.: Opening the black box - data driven visualization of neural networks. In Proceedings of IEEE Visualization (2005), pp. 383-390. 13
174. TATU A., MAAS F., FARBER I., BERTINI E., SCHRECK T., SEIDL T., KEIM D.: Subspace search and visualization to make sense of alternative clusterings in high-dimensional data. In IEEE Conference on Visual Analytics Science and Technology (2012), IEEE, pp. 63-72. 5, 11, 12, 13
175. TORSNEY-WEIR T., SAAD A., MOLLER T., HEGE H.-C., WEBER B., VERBAVATZ J., BERGNER S.: Tuner: Principled parameter finding for image segmentation algorithms using visual response surface exploration. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 1892-1901. 5
176. VAN DEN ELZEN S., VAN WIJK J.: Baobabview: Interactive construction and analysis of decision trees. In IEEE Conference on Visual Analytics Science and Technology (2011), pp. 151-160. 13
177. VIDAL R.: A tutorial on subspace clustering. IEEE Signal Processing Magazine (2011). 5, 13
178. WILKINSON L., ANAND A., GROSSMAN R.: Graph-theoretic scagnostics. In IEEE Symposium on Information Visualization (2005), vol. 0, p. 21. 7, 11, 12
179. WILKINSON L., ANAND A., GROSSMAN R.: High-dimensional visual analytics: Interactive exploration guided by pairwise views of point distributions. IEEE Transactions on Visualization and Computer Graphics 12, 6 (2006), 1363-1372. 7, 13
180. WARD M. O.: Xmdvtool: Integrating multiple methods for visualizing multivariate data. In Proceedings of IEEE Visualization (1994), pp. 326-333. 3
181. WARD M. O.: Multivariate data glyphs: Principles and practice. In Handbook of Data Visualization. Springer, 2008, pp. 179-198. 8
182. WATTENBERG M.: A note on space-filling visualizations and space-filling curves. In IEEE Symposium on Information Visualization (2005), pp. 181-186. 9
183. WONG P. C., BERGERON R. D.: 30 years of multidimensional multivariate visualization. In Proceedings of Scientific Visualization, Overviews, Methodologies, and Techniques (1994), pp. 3-33. 1
184. WEBER G., BREMER P.-T., PASCUCCI V.: Topological landscapes: A terrain metaphor for scientific data. IEEE Transactions on Visualization and Computer Graphics 13, 6 (2007), 1416-1423. 9
185. WEBER G. H., BREMER P.-T., PASCUCCI V.: Topological cacti: Visualizing contour-based statistics. Topological Methods in Data Analysis and Visualization II Mathematics and Visualization (2012), 63-76. 9
186. WEAVER C.: Conjunctive visual forms. IEEE Transactions on Visualization and Computer Graphics 15, 6 (2009), 929-936. 3
187. WILLIAMS M., MUNZNER T.: Steerable, progressive multidimensional scaling. In IEEE Symposium on Information Visualization (2004), pp. 57-64. 4, 11, 12
188. WADDELL A., OLDFORD R. W.: RnavGraph: A visualization tool for navigating through high-dimensional data. 10
189. WANG J., PENG W., WARD M. O., RUNDENSTEINER E. A.: Interactive hierarchical dimension ordering, spacing and filtering for exploration of high dimensional datasets. In IEEE Symposium on Information Visualization (2003), IEEE, pp. 105-112. 9
190. WANG B., SUMMA B., PASCUCCI V., VEJDEMOJOHANSSON M.: Branching and circular features in high dimensional data. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 1902-1911. 6, 14
191. YUAN X., GUO P., XIAO H., ZHOU H., QU H.: Scattering points in parallel coordinates. IEEE Transactions on Visualization and Computer Graphics 15, 6 (2009), 1001-1008. 8, 10, 12
192. YANG J., HUBBALL D., WARD M. O., RUNDENSTEINER E. A., RIBARSKY W.: Value and relation display: interactive visual exploration of large data sets with hundreds of dimensions. IEEE Transactions on Visualization and Computer Graphics 13, 3 (2007), 494-507. 9
193. YANG J., PATRO A., SHIPING H., MEHTA N., WARD M., RUNDENSTEINER E.: Value and relation display for interactive exploration of high dimensional datasets. In IEEE Symposium on Information Visualization (2004), pp. 73-80. 9
194. YUAN X., REN D., WANG Z., GUO C.: Dimension projection matrix/tree: Interactive subspace visual exploration and analysis of high dimensional data. IEEE Transactions on Visualization and Computer Graphics 19, 12 (2013), 2625-2633. 4, 11
195. YANG J., WARD M. O., RUNDENSTEINER E. A.: Interring: An interactive tool for visually navigating and manipulating hierarchical structures. In IEEE Symposium on Information Visualization (2002), IEEE, pp. 77-84. 9
196. 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. 11, 13
197. ZIEGLER H., JENNY M., GRUSE T., KEIM D.: Visual market sector analysis for financial time series data. In IEEE Symposium on Visual Analytics Science and Technology (2010), pp. 83-90. 3
198. ZOMORODIAN A. J.: Topology for Computing (Cambridge Monographs on Applied and Computational Mathematics). Cambridge University Press, 2005. 6
199. ZAIXIAN X., SHIPING H., WARD M., RUNDENSTEINER E.: Exploratory visualization of multivariate data with variable quality. In IEEE Symposium on Visual Analytics Science and Technology (2006), pp. 183-190. 14