Information Visualization for Knowledge Discovery

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Talk at Chulalongkorn Business School (CBS), Bangkok, Thailand

Sep 18, 2012

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Information Visualization for Knowledge Discovery

  1. 1. INFORMATION VISUALIZATIONFor knowledge discoveryKrist wongsuphasawat@kristwongzComputer Engineering, Chulalongkorn University (Intania87, CP30)Dept. of Computer Science & Human-Computer Interaction Lab, Univ. of MarylandData Visualization Scientist, Twitter
  2. 2. data
  3. 3. INFORMATION VISUALIZATIONINFO. VIS.Data visualizationvisualization
  4. 4. A picture is worth a thousand words.
  5. 5. INFORMATION VISUALIZATION Data picture!
  6. 6. INFORMATION VISUALIZATIONINFO. VIS. “ Using visual representations and interaction techniques, which take advantage of the human eye’s broad bandwidth pathway into the mind, to allow users to see, explore, and understand large amounts of information at once.” [Wikipedia]
  7. 7. INFORMATION VISUALIZATION Visual representation
  8. 8. Anscombe s quartet #1 #2 #3 #4 X Y X Y X Y X Y10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.588.0 6.95 8.0 8.14 8.0 6.77 8.0 5.7613.0 7.58 13.0 8.74 13.0 12.74 8.0 7.719.0 8.81 9.0 8.77 9.0 7.11 8.0 8.8411.0 8.33 11.0 9.26 11.0 7.81 8.0 8.4714.0 9.96 14.0 8.10 14.0 8.84 8.0 7.046.0 7.24 6.0 6.13 6.0 6.08 8.0 5.254.0 4.26 4.0 3.10 4.0 5.39 19.0 12.5012.0 10.84 12.0 9.13 12.0 8.15 8.0 5.567.0 4.82 7.0 7.26 7.0 6.42 8.0 7.915.0 5.68 5.0 4.74 5.0 5.73 8.0 6.89
  9. 9. Anscombe s quartet#1 #2 #3 #4 Property Value Mean of X 11.0 Variance of X 10.0 Mean of Y 7.5 Variance of Y 3.75 Correlation between X and Y 0.816 Linear regression y = 3.0 +0.5x Identical statistics
  10. 10. Anscombe s quartet #1 #2 #3 #412! 10! 14! 14! 9!10! 12! 12! 8! 7! 10! 10! 8! 6! 8! 8! 6! 5! 4! 6! 6! 4! 3! 4! 4! 2! 2! 2! 2! 1! 0! 0! 0! 0! 0! 5! 10! 15! 0! 5! 10! 15! 0! 5! 10! 15! 0! 10! 20! But very different
  11. 11. map of napoleon’s marchminard, 1812 •  geography •  course •  time •  direction •  temperature •  quantity of troops
  12. 12. London CholeraOutbreakjohn Snow, 1854
  13. 13. London CholeraOutbreakjohn Snow, 1854
  14. 14. crayons
  15. 15. toysboys girls
  16. 16. INFORMATION VISUALIZATION Visual representation + User interactions click, drag, zoom, select, change color, etc.! !
  17. 17. INFORMATION VISUALIZATION =Mantra= Overview first Zoom and filter Details on demand
  18. 18. Stock marketMap of the market
  19. 19. size = market capStock A Stock B
  20. 20. size = market capStock A Stock B color = price change
  21. 21. Map of the Market
  22. 22. Market!falls!steeply!Feb!27,!2007,!! with!one!excep:on! Market falls 311 points July 26, 2007, with a few exceptions
  23. 23. Market falls 311 points July 26, 2007, with a few exceptions
  24. 24. Market mixed, October 22, 2007
  25. 25. http://www.smartmoney.com/map-of-the-market/
  26. 26. http://www.smartmoney.com/map-of-the-market/
  27. 27. newsmaphttp://newsmap.jp/
  28. 28. Disk inventory x http://www.derlien.com/
  29. 29. Social network relationships http://www.cs.umd.edu/hcil/socialaction
  30. 30. Person A Person B
  31. 31. Has a relationshipPerson A Person B
  32. 32. Strong relationshipPerson A Person B
  33. 33. Strong relationshipPerson A Person B
  34. 34. Person A Person B
  35. 35. Video demo SocialAction
  36. 36. How people are connected on facebook by countryh;p://www.facebookstories.com/stories/1574/#color=con:nent&story=1&country=US!
  37. 37. How people are connected on facebook by countryh;p://www.facebookstories.com/stories/1574/#color=con:nent&story=1&country=US!
  38. 38. GeographicNew york taxi
  39. 39. h;p://www.ny:mes.com/interac:ve/2010/04/02/nyregion/taxiKmap.html!
  40. 40. Interactive charts Baby name voyager http://www.babynamewizard.com/voyager
  41. 41. temporal Data time time time
  42. 42. event! event! event! event! event! event!event! event! LIFE event! event! event! event! event! event! event! event!
  43. 43. Time Event type!( 7:00 am, Wake up ) event! event! event! event! event! event!event! event! LIFE event! event! event! event! event! event! event! event!
  44. 44. event! event! event! event! event! event!event! event! LIFE event! event! event! event! event! event! event! event! “Event Sequence”
  45. 45. Electronic health records( 7:00 am, Wake up ) ( 7:10 am, Shower ) ( 7:30 am, Breakfast )
  46. 46. Electronic health records( 8:40 am, Arrival ) ( 8:50 am, ER) ( 9:15 am, ICU )
  47. 47. Event SequencesMedical TransportationSports EducationWeb logs Logistics and more…
  48. 48. Patient transfersARRIVAL Arrive the hospitalEMERGENCY Emergency roomICU Intensive Care UnitFLOOR Normal roomEXIT-ALIVE Leave the hospital aliveEXIT-DEAD Leave the hospital dead
  49. 49. Save more lives! Pa:ent!ID:!45851733 !! Pa:ent!ID:!45851732 !!12/02/2008!14:26 !Arrival! Pa:ent!ID:!45851731 !!12/02/2008!14:26 !Emergency! 12/02/2008!14:26 !Arrival! Emergency Department 6,000+12/02/2008!22:44 !ICU! 12/02/2008!14:26 !Emergency! 12/02/2008!14:26 !Arrival!12/05/2008!05:07 !Floor! 12/02/2008!22:44 !ICU! 12/02/2008!14:26 !Emergency!12/08/2008!10:02 !Floor! 12/05/2008!05:07 !Floor! 12/02/2008!22:44 !ICU!12/14/2008!06:19 !Discharge! 12/08/2008!10:02 !Floor! 12/05/2008!05:07 !Floor!! 12/14/2008!06:19 !Discharge! 12/08/2008!10:02 !Floor! ! 12/14/2008!06:19 !Discharge! patients per month !
  50. 50. What happened to the patients? Arrival ? ICU ? ?
  51. 51. Video demoCreating LifeFlow
  52. 52. LifeFlow
  53. 53. Video demoData Analysis with LifeFlow
  54. 54. INFORMATION VISUALIZATION Visual representation + User interactions click, drag, zoom, select, change color, etc.! !
  55. 55. INFORMATION VISUALIZATION classified by Network Data types1D: Linear Tree 2D: Map Temporal 3D: Molecules, Biology Multi dimensional (4+ D)
  56. 56. Benefits ofINFORMATION VISUALIZATIONDATA ANALYSIS PRESENTATIONDetect pattern, trend, outliers! Communicate!
  57. 57. DATA ANALYSIS
  58. 58. presentation
  59. 59. presentation
  60. 60. Drawbacks: misleading
  61. 61. Drawbacks: misleading (2)
  62. 62. DATA INFORMATION VISUALIZATION Visual representation + User interactions DATA ANALYSIS PRESENTATION Detect pattern, trend, outliers! Communicate!Krist wongsuphasawat krist.wongz@gmail.com@kristwongz http://kristw.yellowpigz.com
  63. 63. Many eyeshttp://services.alphaworks.ibm.com/manyeyes/app
  64. 64. DATA INFORMATION VISUALIZATION Visual representation + User interactions DATA ANALYSIS PRESENTATION Detect pattern, trend, outliers! Communicate!Krist wongsuphasawat krist.wongz@gmail.com@kristwongz http://kristw.yellowpigz.com
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