Critical Practice Information Design at Luca - Campus Sint Lukas Brussels

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)

121. 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.

122. 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.

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/

146. 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/

147. 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/

149. 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