Introduction to Information Visualization (Part 2)

1. Critical Practice II: Dataviz Luca - Campus Sint-Lukas Brussel a/prof. Andrew Vande Moere Department of Architecture, Urbanism & Planning - ASRO - KU Leuven ------.----------@asro.kuleuven.be - http://infosthetics.com - @infosthetics

2. Prof. Hans Rosling - Talk at TED Conference 2006

3. information visualisation “... is the use of computer- supported, interactive, visual representations of abstract data to amplify cognition” Information Visualization Definition

4. “information visualisation is the use of computer-supported, interactive, visual representations of abstract data to amplify cognition” . automatic/automated algorithm . versus custom or hand-made (e.g. sketching!) . facilitates dealing with highly ‘complex’ data

5. “information visualisation is the use of computer-supported, interactive, visual representations of abstract data to amplify cognition” . to make assumptions, test hypotheses . to allow individualized exploration scenarios . while and during the exploration itself

6. “Overview, zoom and filter, then details on demand” (Schneiderman’s Information Seeking Mantra) Subsets: sorting, filtering, browsing/ exploring, comparing, characterizing trends and distributions, finding trend, patterns, anomalies and outliers, ...

7. “Focus + Context” enables overview (context, at reduced detail) and detailed information (focus, in greater detail) simultaneously, without occlusion. It allows the user to show detailed informations linked with the context, by also having the possibility to focus on other informations by interacting with the system. Combined either via “Time” (sequentially” or “Space” (different portions of the screen estate).

8. “Brushing” is selecting a subset of the data items with an input device (mouse). This is usually done to highlight this subset, but it can also be done to delete it from the view or to de-emphasize it, if the user wants to focus on the other items. (Voigt, 2002) “Linking” causes the brush effect (highlighting, etc.) to be applied on those points in the other plots that represent the same data items.

9. “information visualisation is the use of computer-supported, interactive, visual representations of abstract data to amplify cognition” . just ‘representing’ values or conveying meaning? . guiding users, show example insights, highlighting . engagement? involvement? immersion?

10. “information visualisation is the use of computer-supported, interactive, visual representations of abstract data to amplify cognition” . data without natural representation . requires metaphor to be perceived . data is “mapped” in visual form

11. “information visualisation is the use of computer-supported, interactive, visual representations of abstract data to amplify cognition” . analytics versus communication . understanding/exploring - telling/persuading . goal: creating insights:

12. . What is Insight? . complex: combining data as synthesis . deep: builds over time, generates other questions . qualitative: not exact, uncertain, subjective, ... . unexpected: unpredictable, creative, ... . relevant: needs expertise around data, has impact “Towards Measuring Insight”, North, 2006

13. .Visualization for Exploration . e.g. information visualization, visual analytics, ... . generating hypotheses during exploration . identifying unpredictable, unexpected, ... patterns .Visualization for Communication . e.g. infographics, visual storytelling, ... . supporting hypotheses during explanation

14. Communication via Visualization (here: more geographical mapping) Small arms and Ammunition http://workshop.chromeexperiments.com/projects/armsglobe/

15. Exploration via Visualization GapMinder World http://www.gapminder.org/world

16. Communication via Visualization (here: more geographical mapping) “The 1 Million Block” - http://www.spatialinformationdesignlab.org/projects.php?id=16 - http://www.spatialinformationdesignlab.org/MEDIA/PDF_04.pdf - http:// www.spatialinformationdesignlab.org/MEDIA/ThePattern.pdf

17. The 1 Million Block

18. The 1 Million Block

20. ThemeRiver - pnl.gov - 1999 http://vis.pnnl.gov/pdf/themeriver99.pdf

21. ThemeRiver - pnl.gov - 1999 http://vis.pnnl.gov/pdf/themeriver99.pdf

22. Stacked Graphs – Geometry & Aesthetics - StreamGraphs - Lee Byron - 2007 http://www.leebyron.com/else/streamgraph/

23. The Ebb and Flow of Movies - The New York Times http://www.nytimes.com/interactive/2008/02/23/movies/20080223_REVENUE_GRAPHIC.html

24. From “research” in visualization to visualization “practice”

25. Movie Narrative Charts - Randall Munroe - xkcd http://xkcd.com/657/large/

26. z Software Evolution Storylines - Ogawa and Ma - 2010 http://www.michaelogawa.com/research/storylines/

27. Software Evolution Storylines - Ogawa and Ma - 2010 http://www.michaelogawa.com/research/storylines/

28. Design Considerations for Optimizing Storyline Visualizations Yuzuru Tanahashi and Kwan-Liu Ma - 2012 http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06327274

29. Design Considerations for Optimizing Storyline Visualizations Yuzuru Tanahashi and Kwan-Liu Ma - 2012 http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06327274

30. From visualization ‘exploration’ to visualization ‘research’

31. Information Visualization Popularity 1. Graphical Power 2. Data “Addiction” 3. Software / Tools Availability 4. Data Availability 5. Cross-Disciplinary Education 6.Wide & Responsible Applications

32. Graphical Power

33. Graphical Power

34. Data Addiction

35. Data Addiction

36. Data Addiction

37. Software Tools Availability MAX/MSP - http://cycling74.com

38. Software Tools Availability Processing - http://processing.org

39. Software Tools Availability VVVV - http://vvvv.org

40. Software Tools Availability OpenFrameWorks - http://openframeworks.cc

41. Software Tools Availability Microsoft Excel

42. Software Tools Availability Google Chart Tools https://developers.google.com/chart/ https://developers.google.com/chart/interactive/docs/examples

43. Software Tools Availability D3.js - http://d3js.org/

44. Software Tools Availability IBM Many Eyes - http://www-958.ibm.com/software/data/cognos/manyeyes/

45. Software Tools Availability Tableau Public - http://www.tableausoftware.com/public/

46. Software Tools Availability Venngage - http://venngage.com/

47. Software Tools Availability Easelly - http://www.easel.ly/

48. Software Tools Availability Infogram - http://infogr.am/

49. Software Tools Matrix (especially Javascript libraries, not tools or software) http://selection.datavisualization.ch/

50. Data Availability Data Gov US - http://data.gov

51. Data Availability Data Gov UK - http://data.gov.uk

52. Data Availability Open Data London - http://data.london.gov.uk/

53. Data Availability Open Data Toronto - http://www.toronto.ca/open/

54. Data Availability Open Data San Francisco - http://datasf.org

55. Data Availability Open Data San Francisco - http://datasf.org

56. Data Availability Open Data Gent - http://data.gent.be/

57. Data Availability Open Data Brussels - http://www.brussel.be/artdet.cfm?id=7191

58. Stamen Travel Time Maps - Commuting Times versus Housing Prices http://www.mysociety.org/2007/more-travel-maps/morehousing

59. Cross-Disciplinary (Visualization) Education and Research Computer Science + Design + Statistics + Geography + Data Mining Applied to genomics, social sciences, economics, life sciences, sustainability, ...

60. data insight 10010110 knowledge transfer data mapping mapping inversion visualisation comprehension ! visual transfer Visual Mapping Methodology

61. Web2DNA http://www.baekdal.com/web2dna/

62. Web2DNA Flickr Collection http://www.flickr.com/photos/tags/web2dna/

63. Choice of “Metaphor” . can be potentially seemingly “useless” . yet receive a lot of interest . how to interpret “useful”? . persuasiveness of visual representations?

64. Visualization as a “Medium” . scientiﬁc visualization . data graphics . infographics . information design . data art

65. 1. (Scientific) Visualization

66. LineAO - Improved Three-Dimensional Line Rendering http://www.informatik.uni-leipzig.de/~ebaum/Publications/eichelbaum2012a/

67. DNA Coiling, Replication, Transcription and Translation - WEHI http://www.youtube.com/watch?v=DA2t5N72mgw

68. 2. Data Graphics Eurovizion - Ben Willers http://lifeindata.site50.net/work/eurovizion/eurovizion.html

69. Statistical Atlases of the United States - 1870-1890 http://www.handsomeatlas.com/

70. The Jobless Rate for People Like You - The New York Times http://www.nytimes.com/interactive/2009/11/06/business/economy/unemployment-lines.html

71. Four Ways to Slice Obama’s 2013 Budget Proposal - The New York Times http://www.nytimes.com/interactive/2012/02/13/us/politics/2013-budget-proposal-graphic.html

72. Spotlight on Profitability - Information is Beautiful Competition Entry (not winning...) http://www.informationisbeautifulawards.com/2012/02/hollywood-visualisation-challenge- design-shortlist/ http://szucskrisztina.hu/images/holly.png

73. 2. Information Graphics

74. Starbucks Coffee Cup vs. Country Origins - Fast Food Revenue vs. Brands

75. Telenet Social Media Report http://blog.telenet.be/wp-content/uploads/2012/01/Telenet-Social-Media-Report-20111.jpg

76. Year Report 2011 - http://feltron.com

77. Debtris - David McCandless / Information is Beautiful http://www.informationisbeautiful.net/2010/debtris/

78. 4. Data Visualization OECD Better Life Index - Moritz Stefaner http://www.oecdbetterlifeindex.org/

79. Flight & Expulsion - Nice One http://www.niceone.org/lab/refugees/

80. Take a Look at Health - Fathom Design http://visualization.geblogs.com/visualization/health_visualizer/

81. 5. Information Design Chromosome 14 - Ben Fry

82. We Feel Fine - Jonathan Harris and Sep Kamvar http://www.wefeelfine.org/

83. WorldShapin - Compare Countries through their Shape - Carlo Zapponi & Vasundhara Parakh http://www.worldshap.in/#/PH/BZ/KE/

84. Notabilia - Visualizing Deletion Discussions on Wikipedia - Moritz Stefaner http://notabilia.net/

85. 6. Information Art DNA Portrait - dna11.com

86. Getting Lost - Marco Bagni http://vimeo.com/37031074

87. TextArc - An Alternative Way to View a Text - Brad Paley http://www.textarc.org/

88. Poetry on the Road 6 - Boris Müller http://www.esono.com/boris/projects/poetry06/

89. DoodleBuzz - A Typographic News Explorer http://www.doodlebuzz.com/

91. Name Trends http://nametrends.net/name.php?name=Andrew

92. Baby Name Wizard - Martin Wattenberg http://www.babynamewizard.com/voyager#

93. 1. The Role of Interaction

94. Amazon Digital Cameras Treemap - The Hive Group http://www.hivegroup.com/demos/amazon/499052.html

95. Newsmap - Marumishi - 2004 http://newsmap.jp/ and http://marumushi.com/projects/newsmap

96. 2. The Role of Aesthetics

97. A Year in Iraq and Afghanistan - The New York Times - 2009 http://www.nytimes.com/2011/01/30/opinion/30casualty-chart.html

98. Faces of the Fallen - Washington Post - 2009 http://apps.washingtonpost.com/national/fallen/

99. UK Casualties in Afghanistan and Iraq - BBC News - 2009 http://www.bbc.co.uk/news/uk-10634102

100. CNN Home and Away - CNN - Stamen Design http://edition.cnn.com/SPECIALS/war.casualties/

101. Monument - Caleb Larsen - 2006 http://caleblarsen.com/

102. Monument - Caleb Larsen - 2006 http://caleblarsen.com/

103. 3. The Role of Data Focus (~ Meaning)

104. Lau A. and Vande Moere A. (2007), "Towards a Model of Information Aesthetic Visualization", IEEE International Conference on Information Visualisation (IV'07), pp. 87-92.

105. Aesthetic Effect in Data Visualization - Nick Cawthon and Andrew Vande Moere - 2007

106. Aesthetic Effect in Data Visualization - Nick Cawthon and Andrew Vande Moere - 2007

107. Aesthetic Effect in Data Visualization - Most Beautiful

108. Aesthetic Effect in Data Visualization - Least Beautiful

109. Aesthetic Effect in Data Visualization - Correct Responses

110. Aesthetic Effect in Data Visualization - Least Correct Responses

111. Aesthetic Effect in Data Visualization - Low Abandonment Rate

112. Aesthetic Effect in Data Visualization - High Abandonment Rate

113. “Reversible” “Factual” Gapminder (2007) Many Eyes (2007) OECD eXplorer (2009)

114. “Irreversible” “Meaningful” Bitalizer (2008) Poetry on the Road (2004) Texone (2005)

115. Partly “Reversible” Partly “Factual” Digg Swarm (2007) ReMap (2009) We Feel Fine (2006)

116. “Analytical” Style (ANA)

117. “Magazine” Style (MAG)

118. “Artistic” Style (ART)

119. Insight Analysis Rating (1 - 5) ANA MAG ART uncertain - conﬁdent 4.10 (1.11) 4.21 (0.87) 4.17 (0.95) difﬁcult - easy 3.78 (1.17) 3.63 (1.29) 4.00 (1.24) shallow - deep 3.18 (1.10) 2.93 (1.08) 2.54 (1.17) shallow – deep (expert rating) 2.44 (0.78) 2.36 (0.70) 2.28 (0.64)

120. Insight Analysis Rating (1 - 5) ANA MAG ART ugly - beautiful 3.48 (0.85) 3.08 (1.03) 3.11 (1.02) obtrusive - ﬂuid 3.27 (0.95) 3.08 (1.01) 2.80 (1.00) ambiguous - clear 3.39 (1.17) 1.98 (0.89) 2.00 (0.86) difﬁcult - easy to understand 3.55 (1.04) 2.08 (1.07) 2.14 (1.07) intended inform – express 2.80 (1.15) 3.54 (1.18) 3.66 (1.06) useless - useful 3.61 (0.95) 2.70 (1.09) 2.45 (0.90) frustrating - enjoyable 3.43 (1.00) 2.54 (1.16) 2.34 (1.06) unusable - usable 3.77 (0.91) 2.78 (1.13) 2.64 (1.12) boring - engaging 3.43 (0.93) 3.10 (0.95) 2.80 (1.00) non-functional - functional 3.93 (0.82) 2.80 (1.18) 2.50 (1.13) tool - art 2.30 (1.07) 3.32 (1.19) 3.68 (0.93)

123. Sketchy Rendering for Information Visualization, Wood et al., 2012 http://tobias.isenberg.cc/personal/papers/Wood_2012_SRI.pdf

124. Sketchy Rendering for Information Visualization, Wood et al., 2012 http://tobias.isenberg.cc/personal/papers/Wood_2012_SRI.pdf

125. Our Irresistible Fascination with All Things Circular http://www.perceptualedge.com/articles/visual_business_intelligence/ our_fascination_with_all_things_circular.pdf

126. Our Irresistible Fascination with All Things Circular http://www.perceptualedge.com/articles/visual_business_intelligence/ our_fascination_with_all_things_circular.pdf

127. “Useful Junk? The Effects of Visual Embellishment on Comprehension and Memorability of Charts”, Bateman et al., http://hci.usask.ca/uploads/173-pap0297-bateman.pdf

128. “Guidelines for designing information charts often state that the presentation should reduce ‘chart junk‘ – visual embellishments that are not essential to understanding the data. In contrast, some popular chart designers wrap the presented data in detailed and elaborate imagery, raising the questions of whether this imagery is really as detrimental to understanding as has been proposed, and whether the visual embellishment may have other beneﬁts. To investigate these issues, we conducted an experiment that compared embellished charts with plain ones, and measured both interpretation accuracy and long-term recall. We found that people‘s accuracy in describing the embellished charts was no worse than for plain charts, and that their recall after a two-to-three-week gap was signiﬁcantly better. Although we are cautious about recommending that all charts be produced in this style, our results question some of the premises of the minimalist approach to chart design.” “Useful Junk? The Effects of Visual Embellishment on Comprehension and Memorability of Charts”, Bateman et al., http://hci.usask.ca/uploads/173-pap0297-bateman.pdf

129. “Useful Junk? The Effects of Visual Embellishment on Comprehension and Memorability of Charts”, Bateman et al., http://hci.usask.ca/uploads/173-pap0297-

130. “The Chart Junk Debate”, Stephen Few http://www.perceptualedge.com/articles/visual_business_intelligence/ the_chartjunk_debate.pdf

131. “Benefitting InfoVis with Visual Difficulties”, Hullman et al. http://misc.si.umich.edu/publications/83

132. Many well-cited theories for visualization design state that a visual representation should be optimized for quick and immediate interpretation by a user. Distracting elements like decorative “chartjunk” or extraneous information are avoided so as not to slow comprehension. Yet several recent studies in visualization research provide evidence that non-efficient visual elements may benefit comprehension and recall on the part of users. Similarly, findings from studies related to learning from visual displays in various subfields of psychology suggest that introducing cognitive difficulties to visualization interaction can improve a user’s understanding of important information. In this paper, we synthesize empirical results from cross-disciplinary research on visual information representations, providing a counterpoint to efficiency-based design theory with guidelines that describe how visual difficulties can be introduced to benefit comprehension and recall. We identify conditions under which the application of visual difficulties is appropriate based on underlying factors in visualization interaction like active processing and engagement. We characterize effective graph design as a trade-off between efficiency and learning difficulties in order to provide Information Visualization (InfoVis) researchers and practitioners with a framework for organizing explorations of graphs for which comprehension and recall are crucial. We identify implications of this view for the design and evaluation of information visualizations. “Benefitting InfoVis with Visual Difficulties”, Hullman et al. http://misc.si.umich.edu/publications/83

133. “Benefitting InfoVis with Visual Difficulties”, Hullman et al. http://misc.si.umich.edu/publications/83

134. A Tour through the Visualization Zoo http://queue.acm.org/detail.cfm?id=1805128

145. Design Study Methodology: Reflections from the Trenches and the Stacks Michael Sedlmair, Miriah Meyer, Tamara Munzner, IEEE Infovis 2012 http://www.cs.ubc.ca/nest/imager/tr/2012/dsm/

148. your technique Design Study Methodology: Reflections from the Trenches and the Stacks Michael Sedlmair, Miriah Meyer, Tamara Munzner, IEEE Infovis 2012 http://www.cs.ubc.ca/nest/imager/tr/2012/dsm/

150. Narrative Visualization: Telling Stories with Data Edward Segel and Jeffrey Heer http://vis.stanford.edu/files/2010-Narrative-InfoVis.pdf Genres of Narrative Visualization, Balancing Author-Driven versus Reader-Driven Stories

151. Narrative Visualization: Telling Stories with Data Edward Segel and Jeffrey Heer http://vis.stanford.edu/files/2010-Narrative-InfoVis.pdf

153. “Welke supermarkt is het goedkoopst?”, De Standaard

154. “Winst van Bedrijven in Groeilanden”, De Standaard

155. “Evolutie Economische Groei”, 2 november 2012

156. “Ondernemersklimaat wereldwijd verbeterd”, De Standaard, 24 oktober 2012

157. “Negen Swing States”, Knack, 24 oktober 2012

158. “Hoeveel Jobs worden gecreeerd bij een indexsprong”, De Standaard

159. “4 Studiemethodes”, De Standaard Online, 10 september 2012

160. “MBA, een goudmijn voor uw carriere”, vacature.com

161. “Evolutie loonkosten in de technologiesector”, De Standaard

162. “Tarieven in België”, Knack, http://www.knack.be/infografiek-hoeveel-kost-een-mooi-lijf/

163. “500 jobs bedreigd”, Het Nieuwsblad, 27 oktober 2012

164. Thank you! Questions? ------.----------@asro.kuleuven.be /// http://infosthetics.com /// @infosthetics

Introduction to Information Visualization (Part 2)

Introduction to Information Visualization (Part 2)

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