Isdt 2010

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Isdt 2010

  1. 1. Tools + strategies for data collection + visualization ISDT 2010
  2. 2. tools to help teams communicate
  3. 3. July 4, 1966
  4. 4. via wikipedia
  5. 5. early 1990s
  6. 6. 2009
  7. 7. Open Gov. Data
  8. 8. Little data: * crime data * parking meeter location * maps + Open Source: * Drupal * Mapnik * Rails
  9. 9. data.octo.dc.gov
  10. 10. www.outsideindc.com
  11. 11. www.stumblesafely.com
  12. 12. Data Visualization Matters
  13. 13. What do you call this?
  14. 14. a positive externality
  15. 15. More effective government
  16. 16. On the ground in Program in Africa Program in Peru Afghanistan USAID in DC Business Military
  17. 17. So who paid for these great tool?
  18. 18. Funding tools Government funding Private sector builds better tools tools Government Data Private Sector
  19. 19. Reinventing Government
  20. 20. November 19th, 2009
  21. 21. twitter.com/ericg via cnn
  22. 22. "Afghanistan is committed to end the culture of impunity and violation of law and bring to justice those involved in spreading corruption and abuse of public property" - President Hamid Karzai 3 hours ago
  23. 23. twitter.com/ericg
  24. 24. twitter.com/ericg
  25. 25. twitter.com/ericg
  26. 26. Data Sources: • Original Polling Center Master list of 6,969 polling centers from the Independent Election Commission (IEC). • IEC's election prelim results from September 16th, a 2,500 page PDF. • The Electoral Complaints Commission's (ECC) complaint data (which aggregates only to the provincial level). twitter.com/ericg
  27. 27. we needed a data browser
  28. 28. www.AfghanistanElectionData.org
  29. 29. The system geo codes votes down the the district level. The political boundaries for this map covered 400 districts. Density point visualization shows results based on the Highlighted stations criteria, in this case % of stations effected.
  30. 30. Complex analysis: This Afghan ethnic distribution base layer is overlaid with districts won by Karzai (red dots) and Abdullah (green dots). Dot size indicates the number of votes. Ethnic data is digitized from the Soviet Atlas Narodov Mira
  31. 31. Interacting with the data: you can quickly drill down to any region, as the map zooms.
  32. 32. • Percent Population Urban by District Population by District (2003-2004) AIMS CSO Population Statistics. • Settled Population by Province (2006-2007) Afghanistan Human Development Report 2007, Center for Policy and Human Development, Kabul University • Estimated votes, via IEC’s Master Polling Center list
  33. 33. Population: 22,700 Estimated voters: 53,039 Difference: 30,339
  34. 34. Total votes: 15,023
  35. 35. Drill down in context: “Highlighted Station” selection continues to work within both provinces + districts
  36. 36. Per polling center data: see the affected stations and votes within a polling center
  37. 37. security matters photo credit boston.com
  38. 38. geography matters via flickr: by www.pictobank.com
  39. 39. Road data: OSM provides better street data than AIMS
  40. 40. twitter.com/ericg via wikimedia.org
  41. 41. Snow line: 1,800 meters according to FAO
  42. 42. Map Data Sources: • Elevation information is from the SRTM (Shuttle Radar Topography Mission) • Road information from OpenStreetMap • Provincial and district data are from AIMS (Afghanistan Information Management Services)
  43. 43. Opening Data with Open Street Maps
  44. 44. Mogadishu- Kinshasa
  45. 45. The OSM Community is Huge and Growing
  46. 46. http://vimeo.com/2598878
  47. 47. Last spring, over 141,000 miles of new mapping data from Africover (FAO) was contributed to OpenStreetMap.com twitter.com/ericg
  48. 48. + 92,817.62 mi Congo- before Congo- after
  49. 49. + 17,212.75 mi Tanzania- before Tanzania- after
  50. 50. + 459.29 mi Rwanda- before Rwanda- after
  51. 51. + 17,212 mi Kenya- before Kenya- after twitter.com/ ericg
  52. 52. + 11,609.51 mi Sudan- before Sudan- after twitter.com/ ericg
  53. 53. + 1,796 mi Burundi- before Burundi- after twitter.com/ ericg
  54. 54. Total + 141,107.17 mi twitter.com/ericg
  55. 55. Making Beautiful Maps From Open Data
  56. 56. Flexible Data Workflow
  57. 57. Offline Mapping
  58. 58. The Future of Data Browsers
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