Introduction to Data Visualisation

1. Data Visualisation
Dr. Andrew Errity
@aerrity

2. What is Data Visualisation?
• The goal is to create graphical representations
of data that communicate information in a clear
and effective manner.
• “The purpose of information visualization is
insight, not pictures”
(Ben Shneiderman, 2011)
• “The goal of visualization is the accurate,
interactive, and intuitive presentation of data.”
(Möller et al., 2009)

3. Data Explosion
http://en.wikipedia.org/wiki/File:Operation_Upshot-Knothole_-_Badger_001.jpg

4. http://flowingdata.com/2010/11/19/target-for-charting-excellence/
Target for Charting Excellence (Nathan Yau, 2010)

5. Form: Static
Form: Interactive
Function:
Exploratory
Function:
Explanatory
Visualisation Types (adapted from Schwabish 2014)

6. Examples

7. William Playfair (1759 - 1823)
• Viewed as the inventor of most of the common
graphs used to display data
– line plots & bar charts (1786)
– pie chart (1801)
• "On inspecting any one of these Charts attentively,
a sufficiently distinct impression will be made, to
remain unimpaired for a considerable time, and
the idea which does remain will be simple and
complete, at once including the duration and the
amount.“
(Playfair, 1786)

8. Trade-balance (William Playfair, 1786)
http://en.wikipedia.org/wiki/File:Playfair_TimeSeries-2.png

9. Scotland's imports and exports in 1781 (William Playfair, 1786)
http://en.wikipedia.org/wiki/File:Playfair_Barchart.gif

10. (Barrow, 2008)
Proportions of the Turkish Empire located in Asia, Europe and Africa
(William Playfair, 1801)

11. http://en.wikipedia.org/wiki/File:Nightingale-mortality.jpg
Causes of Death in the Crimean War (Florence Nightingale, 1858)

12. • First flow map
• Line thickness
represents the
traffic between
Irish cities
(Thrower, 2008)
Traffic Flow (Henry D. Harness , 1837)

13. • First known
example of a
proportional
symbol map
• Differently sized
circles showing
population
density centred
at various Irish
cities.
(Thrower, 2008)
Irish Population Density (Henry D. Harness , 1837)

14. (Tufte, 1997)
Cholera Map (John Snow, 1854)

15. (Tufte, 1983)
Napoleon’s March on Moscow (Charles J. Minard, 1869)

16. Moritz Stefaner, Frank Rausch, Jonas Leist, Marcus Paeschke, Dominikus Baur and Timm Kekeritz for Raureif GmbH, Berlin.
OECD Better Life Index (Moritz Stefaner et al., 2013) -
http://www.oecdbetterlifeindex.org

17. US Gun Deaths (Periscopic, 2013) - http://guns.periscopic.com

18. Earth (Cameron Beccario, 2013) - http://earth.nullschool.net

19. Key Principles

20. Edward Tufte
• Professor emeritus at Yale
• “Excellence in statistical graphics consists of
complex ideas communicated with clarity,
precision, and efficiency.”
(Tufte, 1983)

21. Excellence and Integrity
• Edward R. Tufte’s (1983) principles of graphical
excellence and integrity
1. Serve a purpose
2. Make large data sets coherent
3. Present many numbers in a small space
4. Don’t lie
5. Use clear labels to defeat ambiguity and
graphical distortion
6. Show entire scales
7. Show in context

22. Scale Distortions
Based on slide by H. Pfister, Harvard
880
900
920
940
960
980
1000
1020
1040
2005 2006 2007 2008 2009 2010

23. • Drop is less than 10%
Scale Distortions – Show Entire Scale
0
200
400
600
800
1000
2005 2006 2007 2008 2009 2010
Based on slide by H. Pfister, Harvard

24. Scale Distortions – Show in Context
0
200
400
600
800
1000
1980 1990 2000 2010
Based on slide by H. Pfister, Harvard

25. Which is Better?
Government payrolls in 1937 (Huff ,1993)

26. Context (1)
Based on slide by H. Pfister, Harvard

27. Context (2)
Based on slide by H. Pfister, Harvard

28. Context (3)
Based on slide by H. Pfister, Harvard

29. Principles of Data Graphics
• Edward R. Tufte’s (1983) principles of data
graphics
1. Above all else show the data
2. Maximize the data-ink ratio
3. Erase non-data-ink
4. Erase redundant data-ink
5. Revise and edit

30. Principles of Data Graphics
• Edward R. Tufte’s (1983) principles of data
graphics - revised
1. Above all else show the data
2. Maximize the data-pixel ratio
3. Erase non-data-pixels
4. Erase redundant data-pixels
5. Revise and edit

31. Redesigns

32. 0
5
10
15
20
25
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Based on slide by H. Pfister, Harvard
Avoid Chartjunk
• Chartjunk: Any extra visual elements that may
distract from the data

33. 0
5
10
15
20
25
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Based on slide by H. Pfister, Harvard

34. 0
5
10
15
20
25
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Based on slide by H. Pfister, Harvard

35. 0
5
10
15
20
25
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Based on slide by H. Pfister, Harvard

36. 0
5
10
15
20
25
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Based on slide by H. Pfister, Harvard

37. 0
5
10
15
20
25
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Based on slide by H. Pfister, Harvard

38. (Schwabish, 2014)

39. (Schwabish, 2014)

40. (Schwabish, 2014)

41. (Schwabish, 2014)

42. (Schwabish, 2014)

43. (Schwabish, 2014)

44. (Schwabish, 2014)

45. (Schwabish, 2014)

46. (Schwabish, 2014)

47. (Schwabish, 2014)

48. Company A Company B Company C
Company D Company E

49. 9%
13%
18% 44%
16%
Company A Company B Company C
Company D Company E

50. http://blog.visual.ly/2ds-company-3ds-a-crowd/

51. Company A Company B Company C
Company D Company E
13%
44%
16%
9%
18%

53. Macworld Expo 2008 Steve Job’s Keynote

54. (Schwabish, 2014)

55. (Schwabish, 2014)

56. (Schwabish, 2014)

57. 5 Layers

58. 5 Layers of a Data Visualisation
From Andy Kirk (@visualisingdata):
1. Data representation
2. Colour and background
3. Animation and interaction
4. Arrangement
5. The annotation layer

59. Tools

61. Tableau Example
• Historic Irish Population Choropleth
– See Demo
• Data from the Central Statistics Office (CSO)
– http://www.cso.ie/en/census/interactivetables/

62. Want to learn more?

63. Certificate in Data Visualisation
• Learn more about Data Vis!
• 10 credits @ Level 8
• Weds 7-9pm for 20 weeks (Oct ’14 – Mar ’15)
• €500
• http://bit.ly/1euXVq8

64. Online Course
• Introduction to Infographics and Data Visualization,
Knight Center for Journalism in the Americas
• Run by Alberto Cairo (@albertocairo)
• Not currently running, but due to commence again in
the near future
• http://open.journalismcourses.org/

65. Web Resources
• http://www.visualisingdata.com
• http://flowingdata.com/
• http://www.informationisbeautiful.net/
• http://infosthetics.com/
• http://junkcharts.typepad.com/
• http://www.thefunctionalart.com/
• http://datastori.es/
• http://wtfviz.net

66. Questions?

67. References
• J. D. Barrow, Cosmic imagery: Key images in the history of science.
Bodley Head, 2008.
• D. Huff, How to Lie With Statistics. W W Norton & Co Inc, 1993.
• T. Möller, B. Hamann, and R. Russell, Mathematical foundations of
scientific visualization, computer graphics, and massive data
exploration. Springer, 2009.
• W. Playfair, The commercial and political atlas. Wallis, 1786.
• J. A. Schwabish, “An Economist's Guide to Visualizing Data,” Journal of
Economic Perspectives, vol. 28, no. 1, pp. 209-234, 2014.
• Ben Shneiderman, 2011 [Online]
http://twitter.com/benbendc/status/53087253454528513
• N. J. W. Thrower, Maps and Civilization: Cartography in Culture and
Society, Third Edition, University Of Chicago Press, 2008.
• E. R. Tufte, The visual display of quantitative information. Graphics
Press, 1983.
• E. R. Tufte, Visual explanations. Graphics Press, 1997.

68. References – Title Slide Images
Clockwise from top-left:
• Cameron Beccario, Earth, 2013. http://earth.nullschool.net
• Andrew Errity, Republic of Ireland Cartogram, 2012.
https://googledrive.com/host/0B5vtcGFLVUFgSXhjMEU5RTBNaUU/
• Moritz Stefaner et al., OECD Better Life Index, 2013. http://www.oecdbetterlifeindex.org
• Moritz Stefaner, Muesli Ingredient Network, 2012. http://moritz.stefaner.eu/projects/musli-
ingredient-network/
• Dan Meth, Trilogy Meter, 2009. http://danmeth.com/post/77471620/my-trilogy-meter-1-in-a-series-
of-pop-cultural
• David McCandless, The Billion Pound o Gram, 2009.
http://www.informationisbeautiful.net/visualizations/the-billion-pound-o-gram/
• CSO, Live Register Data, 2014.
http://www.cso.ie/en/releasesandpublications/er/lr/liveregistermarch2014/
• Lee Byron, LastFM Steam Graph, 2008. http://megamu.com/lastfm/
• New York Times, 512 Paths to the White House, 2012.
http://www.nytimes.com/interactive/2012/11/02/us/politics/paths-to-the-white-house.html
• Jon Snow, Cholera Map, 1854. http://www.udel.edu/johnmack/frec682/cholera/snow_map.png
• New York Times, Drought’s Footprint, 2012.
http://www.nytimes.com/interactive/2012/07/20/us/drought-footprint.html
• Mike Bostock, Force-directed graph, 2012. http://bl.ocks.org/mbostock/4062045

69. References – Tools
• Processing - http://www.processing.org/
• D3 - http://d3js.org/
• Raw - http://raw.densitydesign.org/
• CartoDB - http://cartodb.com/
• Tableau - http://www.tableausoftware.com/
• MS Excel - http://office.microsoft.com/en-
ie/microsoft-excel-spreadsheet-software-
FX010048762.aspx
• Adobe Creative Cloud -
https://creative.adobe.com/