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#dcdataviz   Dave Leonard, Phase2 Technology
What I DoSolutions Architect at Phase2 working on large-scale Drupal implementations            #dcdataviz
What I DoSolutions Architect at Phase2 working on large-scale Drupal implementations• Requirements Elicitation    • User E...
What I Don’t Do  #dcdataviz
What I Don’t Do                 Write code               Act pretentious  #dcdataviz
Why We’re HereData visualization concepts, strategies, examples and tools (primarily open-source)                #dcdataviz
The ChallengeMassive amounts of data becoming available, how do we make sense of it all?            #dcdataviz
The Challenge Massive amounts of data becoming available, how do we make sense of it all?Semantic Web                Open ...
Data vs Display“What” variables were measured vs “how” you visually represent them         #dcdataviz
Types of Data              Quantitative and qualitative #dcdataviz                                  Data vs Display
Quantitative Data     Precise, standardized numerical measurements   #dcdataviz                               Data vs Disp...
Quantitative Data                     Precise, standardized numerical measurements3.75 mph average                98° 17’ ...
Qualitative Data  Categorical data with varying degrees of precision  #dcdataviz                                 Data vs D...
Qualitative Data                             Categorical data with varying degrees of precision40% of Arlington residents ...
Using Qualitative      Data Establish a quantifiable spectrum for collection and presentation       #dcdataviz            ...
Using Qualitative      Data Establish a quantifiable spectrum for collection and presentation         On a 1 - 10 scale, h...
Display“How” dimensions are visually represented (other than text)    #dcdataviz                                 Data vs D...
Display         “How” dimensions are visually represented (other than text)Width              Position (x,y,z)            ...
Data + DisplayMapping data dimensions to visual representations intuitively     #dcdataviz
FATA: Inside Pakistan’s Tribal Regions             http://preparedness.interaction.org/#dcdataviz                         ...
FATA: Inside Pakistan’s Tribal Regions             http://preparedness.interaction.org/#dcdataviz                         ...
Visual NoiseExcessive visual stimuli that distract from the intended purpose      #dcdataviz
#dcdataviz   Visual Noise
“                 The most important consideration whendesigning for efficiency is that every bit of visual content willma...
#dcdataviz   Visual Noise
#dcdataviz   Visual Noise
#dcdataviz   Visual Noise
#dcdataviz   Visual Noise
“                    You’re showing me a lot, but what are youtrying to say?         - Your Brain, excerpted from “Why Sho...
#dcdataviz   Visual Noise
#dcdataviz   Visual Noise
#dcdataviz   Visual Noise
#dcdataviz   Visual Noise
#dcdataviz   Visual Noise
#dcdataviz   Visual Noise
#dcdataviz   Visual Noise
#dcdataviz   Visual Noise
Presentations    Demonstrative vs investigative visualizations #dcdataviz
Presentations                    Demonstrative vs investigative visualizationsLess User                                   ...
Demonstrative              AUTHOR dictates your conclusions #dcdataviz
#dcdataviz   Demonstrative Presentations
#dcdataviz   Demonstrative Presentations
#dcdataviz   Demonstrative Presentations
#dcdataviz   Demonstrative Presentations
#dcdataviz   Demonstrative Presentations
Investigative  Empowering YOU to draw your own conclusions#dcdataviz
#dcdataviz   Investigative Presentations
#dcdataviz   Investigative Presentations
#dcdataviz   Investigative Presentations
#dcdataviz   Investigative Presentations
#dcdataviz   Investigative Presentations
#dcdataviz   Investigative Presentations
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Data Visualization Strategies and Open Source Solutions

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This presentation was given by Dave Leonard from Phase2 Technology at Refresh DC on April 21.

http://refresh-dc.org/

http://www.phase2technology.com/people/dave

Published in: Technology, Education
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Data Visualization Strategies and Open Source Solutions

  1. 1. #dcdataviz Dave Leonard, Phase2 Technology
  2. 2. What I DoSolutions Architect at Phase2 working on large-scale Drupal implementations #dcdataviz
  3. 3. What I DoSolutions Architect at Phase2 working on large-scale Drupal implementations• Requirements Elicitation • User Exp and Info Arch • Customer Training• Drupal Consulting • Content Migration Planning • Break Stuff (QA) #dcdataviz
  4. 4. What I Don’t Do #dcdataviz
  5. 5. What I Don’t Do Write code Act pretentious #dcdataviz
  6. 6. Why We’re HereData visualization concepts, strategies, examples and tools (primarily open-source) #dcdataviz
  7. 7. The ChallengeMassive amounts of data becoming available, how do we make sense of it all? #dcdataviz
  8. 8. The Challenge Massive amounts of data becoming available, how do we make sense of it all?Semantic Web Open Government and Other Better Methods (i.e. APIs) Transparency Initiatives #dcdataviz
  9. 9. Data vs Display“What” variables were measured vs “how” you visually represent them #dcdataviz
  10. 10. Types of Data Quantitative and qualitative #dcdataviz Data vs Display
  11. 11. Quantitative Data Precise, standardized numerical measurements #dcdataviz Data vs Display
  12. 12. Quantitative Data Precise, standardized numerical measurements3.75 mph average 98° 17’ 15” N, 45° 10’ 6” W 9.85 mi traveled speed #dcdataviz Data vs Display
  13. 13. Qualitative Data Categorical data with varying degrees of precision #dcdataviz Data vs Display
  14. 14. Qualitative Data Categorical data with varying degrees of precision40% of Arlington residents are 60% of Arlington residents 87% of DC residents satisfied with their living vote Democrat are US Citizens situation #dcdataviz Data vs Display
  15. 15. Using Qualitative Data Establish a quantifiable spectrum for collection and presentation #dcdataviz Data vs Display
  16. 16. Using Qualitative Data Establish a quantifiable spectrum for collection and presentation On a 1 - 10 scale, how satisfied are you with living in Arlington? (1 = not satisfied, 5 = somewhat satisfied, 10 = extremely satisfied) #dcdataviz Data vs Display
  17. 17. Display“How” dimensions are visually represented (other than text) #dcdataviz Data vs Display
  18. 18. Display “How” dimensions are visually represented (other than text)Width Position (x,y,z) Color* IconsLength Radius Opacity Shapes #dcdataviz Data vs Display
  19. 19. Data + DisplayMapping data dimensions to visual representations intuitively #dcdataviz
  20. 20. FATA: Inside Pakistan’s Tribal Regions http://preparedness.interaction.org/#dcdataviz Data + Display
  21. 21. FATA: Inside Pakistan’s Tribal Regions http://preparedness.interaction.org/#dcdataviz Data + Display
  22. 22. Visual NoiseExcessive visual stimuli that distract from the intended purpose #dcdataviz
  23. 23. #dcdataviz Visual Noise
  24. 24. “ The most important consideration whendesigning for efficiency is that every bit of visual content willmake it take longer to find any particular element in thevisualization. - Noah Iliinsky, excerpted from “Beautiful Visualization: How To Make it Efficient” http://is.gd/Qc1BWF #dcdataviz Visual Noise
  25. 25. #dcdataviz Visual Noise
  26. 26. #dcdataviz Visual Noise
  27. 27. #dcdataviz Visual Noise
  28. 28. #dcdataviz Visual Noise
  29. 29. “ You’re showing me a lot, but what are youtrying to say? - Your Brain, excerpted from “Why Should I Care About What I’m Looking At?” #dcdataviz Visual Noise
  30. 30. #dcdataviz Visual Noise
  31. 31. #dcdataviz Visual Noise
  32. 32. #dcdataviz Visual Noise
  33. 33. #dcdataviz Visual Noise
  34. 34. #dcdataviz Visual Noise
  35. 35. #dcdataviz Visual Noise
  36. 36. #dcdataviz Visual Noise
  37. 37. #dcdataviz Visual Noise
  38. 38. Presentations Demonstrative vs investigative visualizations #dcdataviz
  39. 39. Presentations Demonstrative vs investigative visualizationsLess User More User Time Time Demonstrative Investigative #dcdataviz
  40. 40. Demonstrative AUTHOR dictates your conclusions #dcdataviz
  41. 41. #dcdataviz Demonstrative Presentations
  42. 42. #dcdataviz Demonstrative Presentations
  43. 43. #dcdataviz Demonstrative Presentations
  44. 44. #dcdataviz Demonstrative Presentations
  45. 45. #dcdataviz Demonstrative Presentations
  46. 46. Investigative Empowering YOU to draw your own conclusions#dcdataviz
  47. 47. #dcdataviz Investigative Presentations
  48. 48. #dcdataviz Investigative Presentations
  49. 49. #dcdataviz Investigative Presentations
  50. 50. #dcdataviz Investigative Presentations
  51. 51. #dcdataviz Investigative Presentations
  52. 52. #dcdataviz Investigative Presentations
  53. 53. #dcdataviz Investigative Presentations
  54. 54. Pave The Way Compelling demonstration spurs investigation #dcdataviz
  55. 55. #dcdataviz Pave The Way
  56. 56. #dcdataviz Pave The Way
  57. 57. #dcdataviz Pave The Way
  58. 58. #dcdataviz Pave The Way
  59. 59. #dcdataviz Pave The Way
  60. 60. #dcdataviz Pave The Way
  61. 61. #dcdataviz Pave The Way
  62. 62. Tools UsedamCharts - Flash and Javascript/HTML5 charts, NOT open source #dcdataviz Pave The Way
  63. 63. Tools UsedamCharts - Flash and Javascript/HTML5 charts, NOT open source #dcdataviz Pave The Way
  64. 64. Tools UsedamCharts - Flash and Javascript/HTML5 charts, NOT open source #dcdataviz Pave The Way
  65. 65. Open SourceEffective presentations built using freely-available, collaborative code #dcdataviz
  66. 66. Mapping Using open source tools#dcdataviz
  67. 67. #dcdataviz Open Source Mapping
  68. 68. #dcdataviz Open Source Mapping
  69. 69. #dcdataviz Open Source Mapping
  70. 70. #dcdataviz Open Source Mapping
  71. 71. #dcdataviz Open Source Mapping
  72. 72. #dcdataviz Open Source Mapping
  73. 73. #dcdataviz Open Source Mapping
  74. 74. #dcdataviz Open Source Mapping
  75. 75. #dcdataviz Open Source Mapping
  76. 76. #dcdataviz Open Source Mapping
  77. 77. Tools#dcdataviz Open Source Mapping
  78. 78. ToolsMapBox, TileMill, and TilestreamHighlighted Features:• Attractive, custom tile designs• Cloud-based storage/delivery of tiles• iPad compatibility for offline viewingLearn More:• http://www.mapbox.com• http://www.developmentseed.com #dcdataviz Open Source Mapping
  79. 79. More MapBox #dcdataviz
  80. 80. #dcdataviz Open Source Mapping
  81. 81. #dcdataviz Open Source Mapping
  82. 82. #dcdataviz Open Source Mapping
  83. 83. #dcdataviz More MapBox
  84. 84. #dcdataviz More MapBox
  85. 85. #dcdataviz More MapBox
  86. 86. #dcdataviz More MapBox
  87. 87. #dcdataviz More MapBox
  88. 88. Charting#dcdataviz
  89. 89. #dcdataviz Open Source Charting
  90. 90. Candlestick Chart#dcdataviz Open Source Charting
  91. 91. ToolsjqPlot - A plotting and charting plugin for the jQuery Javascript frameworkHighlighted Features: Candlestick Chart Code Sample:• Tool tip support• Drag and drop of data points in UI• Computed trend linesLearn More:• http://is.gd/G3qXxT #dcdataviz Open Source Charting
  92. 92. Trending#dcdataviz
  93. 93. #dcdataviz Open Source Trending
  94. 94. #dcdataviz Open Source Trending
  95. 95. #dcdataviz Open Source Trending
  96. 96. #dcdataviz Open Source Trending
  97. 97. #dcdataviz Open Source Trending
  98. 98. Tools Usedflot - jQuery-based Javascript libraryHighlighted Features: Learn More:• Drupal integration via Flot module http://code.google.com/p/flot• Interactive charts with tooltip Development Seed Blog Postsupport http://is.gd/LvYXsM• Panning and zooming capabilities #dcdataviz Open Source Trending
  99. 99. Timelines#dcdataviz
  100. 100. #dcdataviz Open Source Timelines
  101. 101. Timeplot - SIMILE Project#dcdataviz Open Source Timelines
  102. 102. Timeplot - SIMILE Project#dcdataviz Open Source Timelines
  103. 103. Tools UsedTimeplot - DHTML/AJAX-based widget for plotting time series and overlay time-based events over themHighlighted Features: Code Sample:• Timelines• Graphing• Layering of event timelines with datatrendingLearn More:• http://www.simile-widgets.org/timeplot/ #dcdataviz Open Source Timelines
  104. 104. Infographics#dcdataviz
  105. 105. #dcdataviz Open Source Infographics
  106. 106. #dcdataviz Open Source Infographics
  107. 107. #dcdataviz Open Source Infographics
  108. 108. Wrap-Up#dcdataviz
  109. 109. Takeaways#dcdataviz
  110. 110. Takeaways• Know your audience and be realistic about their attention span. #dcdataviz
  111. 111. Takeaways• Know your audience and be realistic about their attention span.• Plan your presentation, THEN figure out what tools you need to execute it. #dcdataviz
  112. 112. Takeaways• Know your audience and be realistic about their attention span.• Plan your presentation, THEN figure out what tools you need to execute it.• Attractive visuals are useless without clearly-defined and executed goals #dcdataviz
  113. 113. Takeaways• Know your audience and be realistic about their attention span.• Plan your presentation, THEN figure out what tools you need to execute it.• Attractive visuals are useless without clearly-defined and executed goals• An abundance of highly-capable, open-source tools is available for you to use andimprove. #dcdataviz
  114. 114. Thank You!Thanks to all who attended, and to these organizations who made this possible: #dcdataviz

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