Table of contents
  1. Story
  2. Slides
    1. Slide 1 Title Slide Census Data Visualization Gallery As Data For the Digital Government Strategy
    2. Slide 2 Background
    3. Slide 3 The 7 Habits of Highly Effective People Habit 2: Begin With The End In Mind
    4. Slide 4 Census Data Visualization Gallery
    5. Slide 5 Census Data Visualization: Knowledge Base
    6. Slide 6 Census Data Visualization: Spreadsheet
    7. Slide 7 Booming Cities Decade to Decade
    8. Slide 8 Booming Cities: Spotfire
    9. Slide 9 Data Visualization Gallery
    10. Slide 10 Population Bracketology
    11. Slide 11 Population Ranking: Spotfire
    12. Slide 12 Net Migration Between California and Other States
    13. Slide 13 Net Migration Between California and Other States: Spotfire
    14. Slide 14 U.S. Territory and Statehood Status by Decade
    15. Slide 15 Statehood Status: Spotfire
    16. Slide 16 Spoken Languages Other than English
    17. Slide 17 Spoken Languages: Spotfire
    18. Slide 18 Center of Population, 1790-2010
    19. Slide 19 Center of Population: Spotfire
    20. Slide 20 Population Change by Decade
    21. Slide 21 Population Change by Decade: Spotfire
    22. Slide 22 Without A High School Education
    23. Slide 23 Without A High School Education: Spotfire
    24. Slide 24 A Decade of State Population Change
    25. Slide 25 A Decade of State Population Change: Spotfire
    26. Slide 26 State-to-State Migrations
    27. Slide 27 State-to-State Migrations: Spotfire
    28. Slide 28 Population by Congressional District
    29. Slide 29 Population by Congressional District: Spotfire
    30. Slide 30 Components of Metro Area Change
    31. Slide 31 Components of Metro Area Change: Spotfire
    32. Slide 32 Blooming States
    33. Slide 33 Blooming States: Spotfire
    34. Slide 34 Largest Urbanized Areas
    35. Slide 35 Largest Urbanized Areas: Spotfire
    36. Slide 36 Coastline County Population
    37. Slide 37 Coastline County Population: Spotfire
    38. Slide 38 I-90 Population Density Profile
    39. Slide 39 I-90 Population Density Profile: Spotfire
    40. Slide 40 Keeping Pace With New York
    41. Slide 41 Keeping Pace With New York: Spotfire
    42. Slide 42 Population Shift
    43. Slide 43 Population Shift: Spotfire
    44. Slide 44 I-10 Population Density Profile
    45. Slide 45 I-10 Population Density Profile: Spotfire
    46. Slide 46 I-5 Population Density Profile
    47. Slide 47 I-5 Population Density Profile: Spotfire
    48. Slide 48 Islands of High Income
    49. Slide 49 Islands of High Income: Spotfire
    50. Slide 50 The Great Migration 1
    51. Slide 51 The Great Migration 2
    52. Slide 52 Following the Frontier Line
    53. Slide 53 Following the Frontier Line: Spotfire
    54. Slide 54 Changing Ranks of States
    55. Slide 55 Changing Ranks of States: Spotfire
    56. Slide 56 Cartograms of State Populations
    57. Slide 57 Cartograms of State Populations: Spotfire
    58. Slide 58 Before and After 1940
    59. Slide 59 Before and After 1940: Spotfire
    60. Slide 60 From Physical to Political Geography
    61. Slide 61 From Physical to Political Geography: Spotfire
    62. Slide 62 Differential City Growth Patterns
    63. Slide 63 Differential City Growth Patterns: Spotfire
    64. Slide 64 I-95 Population Density Profile
    65. Slide 65 I-95 Population Density Profile: Spotfire
    66. Slide 66 Increasing Urbanization
    67. Slide 67 Increasing Urbanization: Spotfire
    68. Slide 68 Gaining and Losing Shares
    69. Slide 69 Gaining and Losing Shares: Spotfire
    70. Slide 70 Top 20 Cities
    71. Slide 71 TIGER Shapefiles: Census Bureau
    72. Slide 72 List of United States Cities: Wikipedia
    73. Slide 73 Albany NY Latitude and Longitude
    74. Slide 74 Top 20 Cities: Spotfire
    75. Slide 75 Conclusions and Recommendations
    76. Slide 76 Conclusions and Recommendations: Spotfire
  3. Spotfire Dashboard
  4. Research Notes
  5. Data Visualization: Images That Tell a Story
    1. Description  
    2. What You'll Learn 
    3. Who Should Attend
    4. About the Presenters
    5. On-Demand Webinar
    6. The Census Bureau’s Data Visualization Mission
      1. Slide 1 The Census Bureau’s Data Visualization Mission
      2. Slide 2 Graphic 1 Slave Population
      3. Slide 3 Graphic 2 Deaths
      4. Slide 4 Graphic 3 Number of Communicants of the Principal Denominations
      5. Slide 5 Graphic 4 Telephone Operator
      6. Slide 6 Graphic 5 Table 86 From Statistical Abstract
      7. Slide 7 Graphic 6 Table 1 From Statistical Abstract
      8. Slide 8 Graphic 7 Table 743 From Statistical Abstract
      9. Slide 9 Satellite Photo 2000 Population Distribution in the United States
      10. Slide 10 American Fact Finder
      11. Slide 11 Readings in Information Visulaization Using Vision Book
      12. Slide 12 The Washingon Post Interactive Graphic
      13. Slide 13 The New York Times Graphics
      14. Slide 14 Show Me the Numbers Book
      15. Slide 15 Creating More Effective Graphics
      16. Slide 16 Data Visualization Team
      17. Slide 17 Inside Census Data Visualization
      18. Slide 18 Census Visualization of the Week
      19. Slide 19 Requirements for a Data Visualization of the Week
      20. Slide 20 Islands of High Income 1 Greater Than $18,000
      21. Slide 21 Islands of High Income 2 Greater Than $70,000
      22. Slide 22 Islands of High Income 3 Greater Than $32,000
    7. U.S. Census Bureau Data Visualization of the Week
      1. Slide 1 Title Slide
      2. Slide 2 Census Visualization Gallery
      3. Slide 3 Data Visualization Parameters
      4. Slide 4 Implications For Production Process
      5. Slide 5 How Do We Put One Of These Together?
      6. Slide 6 Concept 1
      7. Slide 7 Concept 2
      8. Slide 8 Data Preparation 1
      9. Slide 9 Data Preparation 2
      10. Slide 10 Rough Graphics 1
      11. Slide 11 Rough Graphics 2
      12. Slide 12 Rough Graphics 3
      13. Slide 13 Storyboard
      14. Slide 14 Final Graphics
      15. Slide 15 Code Development 1
      16. Slide 16 Code Development 2
      17. Slide 17 Web Presentation
      18. Slide 18 Tips for Concept
      19. Slide 19 Tips for Production
      20. Slide 20 Tips for Process
      21. Slide 21 Samples From The Gallery
      22. Slide 22 Questions?
    8. Transcript
      1. Introduction
      2. Eric Newberger
      3. Marc Perry
      4. Alex Tait
      5. Jean Holmes
      6. Questions and Answers
        1. Section 508 Accessibility
        2. Census Flows Mapper
        3. Values of a Visualization
        4. Makeup of Team
        5. Favorire Visualization Sites
      7. Conclusion
  6. Marc J. Perry Chief, Population Distribution Branch
  7. Population Change in U.S. Counties and Metro Areas, Marc Perry, U.S. Census Bureau
  8. Press Kit: 2012 County/Metro Population Estimates
  9. Data Visualization Gallery
    1. Population Bracketology
    2. Migration Between Calif. & Other States
    3. U.S. Territory and Statehood Status
    4. Spoken Languages Other than English
    5. Center of Population, 1790-2010
    6. Population Change by Decade
    7. Without A High School Education
    8. A Decade of State Population Change
    9. State-to-State Migration
    10. Population Under Age 5 by Congressional District
    11. Components of Metro Area Change
    12. Blooming States
    13. Largest Urbanized Areas
    14. Coastline County Population
    15. I-90 Population Density Profile, 2010
    16. Keeping Pace with New York
    17. Population Shift to the West and South
    18. I-10 Population Density Profile, 2010
    19. Booming Cities, 1830-2010
    20. I-5 Population Density Profile, 2010
    21. Islands of High Income
    22. The Great Migration, 1910 to 1970
    23. Following the Frontier Line, 1790 to 1890
    24. Changing Ranks of States
    25. State Populations: 1890, 1950, and 2010
    26. Before and After 1940
    27. Physical to Political Geography
    28. Differential City Growth Patterns
    29. I-95 Population Density Profile
    30. Increasing Urbanization
    31. Gaining and Losing Shares
    32. Top 20 Cities

Census Data Visualization

Last modified
Table of contents
  1. Story
  2. Slides
    1. Slide 1 Title Slide Census Data Visualization Gallery As Data For the Digital Government Strategy
    2. Slide 2 Background
    3. Slide 3 The 7 Habits of Highly Effective People Habit 2: Begin With The End In Mind
    4. Slide 4 Census Data Visualization Gallery
    5. Slide 5 Census Data Visualization: Knowledge Base
    6. Slide 6 Census Data Visualization: Spreadsheet
    7. Slide 7 Booming Cities Decade to Decade
    8. Slide 8 Booming Cities: Spotfire
    9. Slide 9 Data Visualization Gallery
    10. Slide 10 Population Bracketology
    11. Slide 11 Population Ranking: Spotfire
    12. Slide 12 Net Migration Between California and Other States
    13. Slide 13 Net Migration Between California and Other States: Spotfire
    14. Slide 14 U.S. Territory and Statehood Status by Decade
    15. Slide 15 Statehood Status: Spotfire
    16. Slide 16 Spoken Languages Other than English
    17. Slide 17 Spoken Languages: Spotfire
    18. Slide 18 Center of Population, 1790-2010
    19. Slide 19 Center of Population: Spotfire
    20. Slide 20 Population Change by Decade
    21. Slide 21 Population Change by Decade: Spotfire
    22. Slide 22 Without A High School Education
    23. Slide 23 Without A High School Education: Spotfire
    24. Slide 24 A Decade of State Population Change
    25. Slide 25 A Decade of State Population Change: Spotfire
    26. Slide 26 State-to-State Migrations
    27. Slide 27 State-to-State Migrations: Spotfire
    28. Slide 28 Population by Congressional District
    29. Slide 29 Population by Congressional District: Spotfire
    30. Slide 30 Components of Metro Area Change
    31. Slide 31 Components of Metro Area Change: Spotfire
    32. Slide 32 Blooming States
    33. Slide 33 Blooming States: Spotfire
    34. Slide 34 Largest Urbanized Areas
    35. Slide 35 Largest Urbanized Areas: Spotfire
    36. Slide 36 Coastline County Population
    37. Slide 37 Coastline County Population: Spotfire
    38. Slide 38 I-90 Population Density Profile
    39. Slide 39 I-90 Population Density Profile: Spotfire
    40. Slide 40 Keeping Pace With New York
    41. Slide 41 Keeping Pace With New York: Spotfire
    42. Slide 42 Population Shift
    43. Slide 43 Population Shift: Spotfire
    44. Slide 44 I-10 Population Density Profile
    45. Slide 45 I-10 Population Density Profile: Spotfire
    46. Slide 46 I-5 Population Density Profile
    47. Slide 47 I-5 Population Density Profile: Spotfire
    48. Slide 48 Islands of High Income
    49. Slide 49 Islands of High Income: Spotfire
    50. Slide 50 The Great Migration 1
    51. Slide 51 The Great Migration 2
    52. Slide 52 Following the Frontier Line
    53. Slide 53 Following the Frontier Line: Spotfire
    54. Slide 54 Changing Ranks of States
    55. Slide 55 Changing Ranks of States: Spotfire
    56. Slide 56 Cartograms of State Populations
    57. Slide 57 Cartograms of State Populations: Spotfire
    58. Slide 58 Before and After 1940
    59. Slide 59 Before and After 1940: Spotfire
    60. Slide 60 From Physical to Political Geography
    61. Slide 61 From Physical to Political Geography: Spotfire
    62. Slide 62 Differential City Growth Patterns
    63. Slide 63 Differential City Growth Patterns: Spotfire
    64. Slide 64 I-95 Population Density Profile
    65. Slide 65 I-95 Population Density Profile: Spotfire
    66. Slide 66 Increasing Urbanization
    67. Slide 67 Increasing Urbanization: Spotfire
    68. Slide 68 Gaining and Losing Shares
    69. Slide 69 Gaining and Losing Shares: Spotfire
    70. Slide 70 Top 20 Cities
    71. Slide 71 TIGER Shapefiles: Census Bureau
    72. Slide 72 List of United States Cities: Wikipedia
    73. Slide 73 Albany NY Latitude and Longitude
    74. Slide 74 Top 20 Cities: Spotfire
    75. Slide 75 Conclusions and Recommendations
    76. Slide 76 Conclusions and Recommendations: Spotfire
  3. Spotfire Dashboard
  4. Research Notes
  5. Data Visualization: Images That Tell a Story
    1. Description  
    2. What You'll Learn 
    3. Who Should Attend
    4. About the Presenters
    5. On-Demand Webinar
    6. The Census Bureau’s Data Visualization Mission
      1. Slide 1 The Census Bureau’s Data Visualization Mission
      2. Slide 2 Graphic 1 Slave Population
      3. Slide 3 Graphic 2 Deaths
      4. Slide 4 Graphic 3 Number of Communicants of the Principal Denominations
      5. Slide 5 Graphic 4 Telephone Operator
      6. Slide 6 Graphic 5 Table 86 From Statistical Abstract
      7. Slide 7 Graphic 6 Table 1 From Statistical Abstract
      8. Slide 8 Graphic 7 Table 743 From Statistical Abstract
      9. Slide 9 Satellite Photo 2000 Population Distribution in the United States
      10. Slide 10 American Fact Finder
      11. Slide 11 Readings in Information Visulaization Using Vision Book
      12. Slide 12 The Washingon Post Interactive Graphic
      13. Slide 13 The New York Times Graphics
      14. Slide 14 Show Me the Numbers Book
      15. Slide 15 Creating More Effective Graphics
      16. Slide 16 Data Visualization Team
      17. Slide 17 Inside Census Data Visualization
      18. Slide 18 Census Visualization of the Week
      19. Slide 19 Requirements for a Data Visualization of the Week
      20. Slide 20 Islands of High Income 1 Greater Than $18,000
      21. Slide 21 Islands of High Income 2 Greater Than $70,000
      22. Slide 22 Islands of High Income 3 Greater Than $32,000
    7. U.S. Census Bureau Data Visualization of the Week
      1. Slide 1 Title Slide
      2. Slide 2 Census Visualization Gallery
      3. Slide 3 Data Visualization Parameters
      4. Slide 4 Implications For Production Process
      5. Slide 5 How Do We Put One Of These Together?
      6. Slide 6 Concept 1
      7. Slide 7 Concept 2
      8. Slide 8 Data Preparation 1
      9. Slide 9 Data Preparation 2
      10. Slide 10 Rough Graphics 1
      11. Slide 11 Rough Graphics 2
      12. Slide 12 Rough Graphics 3
      13. Slide 13 Storyboard
      14. Slide 14 Final Graphics
      15. Slide 15 Code Development 1
      16. Slide 16 Code Development 2
      17. Slide 17 Web Presentation
      18. Slide 18 Tips for Concept
      19. Slide 19 Tips for Production
      20. Slide 20 Tips for Process
      21. Slide 21 Samples From The Gallery
      22. Slide 22 Questions?
    8. Transcript
      1. Introduction
      2. Eric Newberger
      3. Marc Perry
      4. Alex Tait
      5. Jean Holmes
      6. Questions and Answers
        1. Section 508 Accessibility
        2. Census Flows Mapper
        3. Values of a Visualization
        4. Makeup of Team
        5. Favorire Visualization Sites
      7. Conclusion
  6. Marc J. Perry Chief, Population Distribution Branch
  7. Population Change in U.S. Counties and Metro Areas, Marc Perry, U.S. Census Bureau
  8. Press Kit: 2012 County/Metro Population Estimates
  9. Data Visualization Gallery
    1. Population Bracketology
    2. Migration Between Calif. & Other States
    3. U.S. Territory and Statehood Status
    4. Spoken Languages Other than English
    5. Center of Population, 1790-2010
    6. Population Change by Decade
    7. Without A High School Education
    8. A Decade of State Population Change
    9. State-to-State Migration
    10. Population Under Age 5 by Congressional District
    11. Components of Metro Area Change
    12. Blooming States
    13. Largest Urbanized Areas
    14. Coastline County Population
    15. I-90 Population Density Profile, 2010
    16. Keeping Pace with New York
    17. Population Shift to the West and South
    18. I-10 Population Density Profile, 2010
    19. Booming Cities, 1830-2010
    20. I-5 Population Density Profile, 2010
    21. Islands of High Income
    22. The Great Migration, 1910 to 1970
    23. Following the Frontier Line, 1790 to 1890
    24. Changing Ranks of States
    25. State Populations: 1890, 1950, and 2010
    26. Before and After 1940
    27. Physical to Political Geography
    28. Differential City Growth Patterns
    29. I-95 Population Density Profile
    30. Increasing Urbanization
    31. Gaining and Losing Shares
    32. Top 20 Cities

  1. Story
  2. Slides
    1. Slide 1 Title Slide Census Data Visualization Gallery As Data For the Digital Government Strategy
    2. Slide 2 Background
    3. Slide 3 The 7 Habits of Highly Effective People Habit 2: Begin With The End In Mind
    4. Slide 4 Census Data Visualization Gallery
    5. Slide 5 Census Data Visualization: Knowledge Base
    6. Slide 6 Census Data Visualization: Spreadsheet
    7. Slide 7 Booming Cities Decade to Decade
    8. Slide 8 Booming Cities: Spotfire
    9. Slide 9 Data Visualization Gallery
    10. Slide 10 Population Bracketology
    11. Slide 11 Population Ranking: Spotfire
    12. Slide 12 Net Migration Between California and Other States
    13. Slide 13 Net Migration Between California and Other States: Spotfire
    14. Slide 14 U.S. Territory and Statehood Status by Decade
    15. Slide 15 Statehood Status: Spotfire
    16. Slide 16 Spoken Languages Other than English
    17. Slide 17 Spoken Languages: Spotfire
    18. Slide 18 Center of Population, 1790-2010
    19. Slide 19 Center of Population: Spotfire
    20. Slide 20 Population Change by Decade
    21. Slide 21 Population Change by Decade: Spotfire
    22. Slide 22 Without A High School Education
    23. Slide 23 Without A High School Education: Spotfire
    24. Slide 24 A Decade of State Population Change
    25. Slide 25 A Decade of State Population Change: Spotfire
    26. Slide 26 State-to-State Migrations
    27. Slide 27 State-to-State Migrations: Spotfire
    28. Slide 28 Population by Congressional District
    29. Slide 29 Population by Congressional District: Spotfire
    30. Slide 30 Components of Metro Area Change
    31. Slide 31 Components of Metro Area Change: Spotfire
    32. Slide 32 Blooming States
    33. Slide 33 Blooming States: Spotfire
    34. Slide 34 Largest Urbanized Areas
    35. Slide 35 Largest Urbanized Areas: Spotfire
    36. Slide 36 Coastline County Population
    37. Slide 37 Coastline County Population: Spotfire
    38. Slide 38 I-90 Population Density Profile
    39. Slide 39 I-90 Population Density Profile: Spotfire
    40. Slide 40 Keeping Pace With New York
    41. Slide 41 Keeping Pace With New York: Spotfire
    42. Slide 42 Population Shift
    43. Slide 43 Population Shift: Spotfire
    44. Slide 44 I-10 Population Density Profile
    45. Slide 45 I-10 Population Density Profile: Spotfire
    46. Slide 46 I-5 Population Density Profile
    47. Slide 47 I-5 Population Density Profile: Spotfire
    48. Slide 48 Islands of High Income
    49. Slide 49 Islands of High Income: Spotfire
    50. Slide 50 The Great Migration 1
    51. Slide 51 The Great Migration 2
    52. Slide 52 Following the Frontier Line
    53. Slide 53 Following the Frontier Line: Spotfire
    54. Slide 54 Changing Ranks of States
    55. Slide 55 Changing Ranks of States: Spotfire
    56. Slide 56 Cartograms of State Populations
    57. Slide 57 Cartograms of State Populations: Spotfire
    58. Slide 58 Before and After 1940
    59. Slide 59 Before and After 1940: Spotfire
    60. Slide 60 From Physical to Political Geography
    61. Slide 61 From Physical to Political Geography: Spotfire
    62. Slide 62 Differential City Growth Patterns
    63. Slide 63 Differential City Growth Patterns: Spotfire
    64. Slide 64 I-95 Population Density Profile
    65. Slide 65 I-95 Population Density Profile: Spotfire
    66. Slide 66 Increasing Urbanization
    67. Slide 67 Increasing Urbanization: Spotfire
    68. Slide 68 Gaining and Losing Shares
    69. Slide 69 Gaining and Losing Shares: Spotfire
    70. Slide 70 Top 20 Cities
    71. Slide 71 TIGER Shapefiles: Census Bureau
    72. Slide 72 List of United States Cities: Wikipedia
    73. Slide 73 Albany NY Latitude and Longitude
    74. Slide 74 Top 20 Cities: Spotfire
    75. Slide 75 Conclusions and Recommendations
    76. Slide 76 Conclusions and Recommendations: Spotfire
  3. Spotfire Dashboard
  4. Research Notes
  5. Data Visualization: Images That Tell a Story
    1. Description  
    2. What You'll Learn 
    3. Who Should Attend
    4. About the Presenters
    5. On-Demand Webinar
    6. The Census Bureau’s Data Visualization Mission
      1. Slide 1 The Census Bureau’s Data Visualization Mission
      2. Slide 2 Graphic 1 Slave Population
      3. Slide 3 Graphic 2 Deaths
      4. Slide 4 Graphic 3 Number of Communicants of the Principal Denominations
      5. Slide 5 Graphic 4 Telephone Operator
      6. Slide 6 Graphic 5 Table 86 From Statistical Abstract
      7. Slide 7 Graphic 6 Table 1 From Statistical Abstract
      8. Slide 8 Graphic 7 Table 743 From Statistical Abstract
      9. Slide 9 Satellite Photo 2000 Population Distribution in the United States
      10. Slide 10 American Fact Finder
      11. Slide 11 Readings in Information Visulaization Using Vision Book
      12. Slide 12 The Washingon Post Interactive Graphic
      13. Slide 13 The New York Times Graphics
      14. Slide 14 Show Me the Numbers Book
      15. Slide 15 Creating More Effective Graphics
      16. Slide 16 Data Visualization Team
      17. Slide 17 Inside Census Data Visualization
      18. Slide 18 Census Visualization of the Week
      19. Slide 19 Requirements for a Data Visualization of the Week
      20. Slide 20 Islands of High Income 1 Greater Than $18,000
      21. Slide 21 Islands of High Income 2 Greater Than $70,000
      22. Slide 22 Islands of High Income 3 Greater Than $32,000
    7. U.S. Census Bureau Data Visualization of the Week
      1. Slide 1 Title Slide
      2. Slide 2 Census Visualization Gallery
      3. Slide 3 Data Visualization Parameters
      4. Slide 4 Implications For Production Process
      5. Slide 5 How Do We Put One Of These Together?
      6. Slide 6 Concept 1
      7. Slide 7 Concept 2
      8. Slide 8 Data Preparation 1
      9. Slide 9 Data Preparation 2
      10. Slide 10 Rough Graphics 1
      11. Slide 11 Rough Graphics 2
      12. Slide 12 Rough Graphics 3
      13. Slide 13 Storyboard
      14. Slide 14 Final Graphics
      15. Slide 15 Code Development 1
      16. Slide 16 Code Development 2
      17. Slide 17 Web Presentation
      18. Slide 18 Tips for Concept
      19. Slide 19 Tips for Production
      20. Slide 20 Tips for Process
      21. Slide 21 Samples From The Gallery
      22. Slide 22 Questions?
    8. Transcript
      1. Introduction
      2. Eric Newberger
      3. Marc Perry
      4. Alex Tait
      5. Jean Holmes
      6. Questions and Answers
        1. Section 508 Accessibility
        2. Census Flows Mapper
        3. Values of a Visualization
        4. Makeup of Team
        5. Favorire Visualization Sites
      7. Conclusion
  6. Marc J. Perry Chief, Population Distribution Branch
  7. Population Change in U.S. Counties and Metro Areas, Marc Perry, U.S. Census Bureau
  8. Press Kit: 2012 County/Metro Population Estimates
  9. Data Visualization Gallery
    1. Population Bracketology
    2. Migration Between Calif. & Other States
    3. U.S. Territory and Statehood Status
    4. Spoken Languages Other than English
    5. Center of Population, 1790-2010
    6. Population Change by Decade
    7. Without A High School Education
    8. A Decade of State Population Change
    9. State-to-State Migration
    10. Population Under Age 5 by Congressional District
    11. Components of Metro Area Change
    12. Blooming States
    13. Largest Urbanized Areas
    14. Coastline County Population
    15. I-90 Population Density Profile, 2010
    16. Keeping Pace with New York
    17. Population Shift to the West and South
    18. I-10 Population Density Profile, 2010
    19. Booming Cities, 1830-2010
    20. I-5 Population Density Profile, 2010
    21. Islands of High Income
    22. The Great Migration, 1910 to 1970
    23. Following the Frontier Line, 1790 to 1890
    24. Changing Ranks of States
    25. State Populations: 1890, 1950, and 2010
    26. Before and After 1940
    27. Physical to Political Geography
    28. Differential City Growth Patterns
    29. I-95 Population Density Profile
    30. Increasing Urbanization
    31. Gaining and Losing Shares
    32. Top 20 Cities

Story

Slides

Background

The 7 Habits of Highly Effective People Habit 2: Begin With The End In Mind

Habit 2 is based on imagination--the ability to envision in your mind what you cannot at present see with your eyes. It is based on the principle that all things are created twice. There is a mental (first) creation, and a physical (second) creation. The physical creation follows the mental, just as a building follows a blueprint. If you don't make a conscious effort to visualize who you are and what you want in life, then you empower other people and circumstances to shape you and your life by default. It's about connecting again with your own uniqueness and then defining the personal, moral, and ethical guidelines within which you can most happily express and fulfill yourself. Begin with the End in Mind means to begin each day, task, or project with a clear vision of your desired direction and destination, and then continue by flexing your proactive muscles to make things happen. 

My Note: My End In Mind Is The Census Data Visualization Gallery As Data For the Digital Government Strategy.
https://www.stephencovey.com/7habits...its-habit2.php

Conclusions and Recommendations

  • The Census Data Visualization Gallery Was Used As An Example of the Digital Government Strategy
    • All Content = Big Data.
  • Spotfire Was Used to Make the Census Visualizations Statistical and Interactive.
    • Spotfire Was Originally Co-developed by Professor Ben Schneiderman, University of Maryland, Who Developed the Treemap, Who Was a Consultant to the Census Bureau.
  • I Responded to Their Invitation to Provide Comments.
    • Specifically, the Concept to “Keep focus on good visual ideas not cutting edge interactivity” Should Be to Focus on Both and To Make the Data More Accessible and Complete.
  • The Census Flow Mapper-Beta is Next.

Slides

Slides

Slide 1 Title Slide Census Data Visualization Gallery As Data For the Digital Government Strategy

http://semanticommunity.info/
http://gov.aol.com/bloggers/brand-niemann/
http://semanticommunity.info/Census_Data_Visualization

BrandNiemann03282013Slide1.PNG

Slide 3 The 7 Habits of Highly Effective People Habit 2: Begin With The End In Mind

https://www.stephencovey.com/7habits...its-habit2.php

BrandNiemann03282013Slide3.PNG

Slide 4 Census Data Visualization Gallery

http://www.census.gov/dataviz/

BrandNiemann03282013Slide4.PNG

 

Slide 5 Census Data Visualization: Knowledge Base

http://semanticommunity.info/Census_Data_Visualization

BrandNiemann03282013Slide5.PNG

Slide 6 Census Data Visualization: Spreadsheet

http://semanticommunity.info/@api/deki/files/23626/CensusVisualizations.xlsx

BrandNiemann03282013Slide6.PNG

Slide 7 Booming Cities Decade to Decade

http://www.census.gov/dataviz/visualizations/017/

BrandNiemann03282013Slide7.PNG

Slide 8 Booming Cities: Spotfire

BrandNiemann03282013Slide8.PNG

Slide 9 Data Visualization Gallery

BrandNiemann03282013Slide9.PNG

Slide 10 Population Bracketology

http://www.census.gov/dataviz/visualizations/057/

BrandNiemann03282013Slide10.PNG

Slide 11 Population Ranking: Spotfire

BrandNiemann03282013Slide11.PNG

Slide 12 Net Migration Between California and Other States

http://www.census.gov/dataviz/visualizations/051/

BrandNiemann03282013Slide12.PNG

Slide 13 Net Migration Between California and Other States: Spotfire

BrandNiemann03282013Slide13.PNG

Slide 14 U.S. Territory and Statehood Status by Decade

http://www.census.gov/dataviz/visualizations/048/

BrandNiemann03282013Slide14.PNG

Slide 15 Statehood Status: Spotfire

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Slide 16 Spoken Languages Other than English

http://www.census.gov/dataviz/visualizations/045/

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Slide 17 Spoken Languages: Spotfire

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Slide 18 Center of Population, 1790-2010

http://www.census.gov/dataviz/visualizations/050/

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Slide 19 Center of Population: Spotfire

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Slide 20 Population Change by Decade

http://www.census.gov/dataviz/visualizations/049/

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Slide 21 Population Change by Decade: Spotfire

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Slide 22 Without A High School Education

http://www.census.gov/dataviz/visualizations/035/

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Slide 23 Without A High School Education: Spotfire

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Slide 24 A Decade of State Population Change

http://www.census.gov/dataviz/visualizations/043/

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Slide 25 A Decade of State Population Change: Spotfire

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Slide 26 State-to-State Migrations

http://www.census.gov/dataviz/visualizations/028/

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Slide 27 State-to-State Migrations: Spotfire

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Slide 28 Population by Congressional District

http://www.census.gov/dataviz/visualizations/034/

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Slide 29 Population by Congressional District: Spotfire

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Slide 30 Components of Metro Area Change

http://www.census.gov/dataviz/visualizations/040/

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Slide 31 Components of Metro Area Change: Spotfire

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Slide 33 Blooming States: Spotfire

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Slide 34 Largest Urbanized Areas

http://www.census.gov/dataviz/visualizations/026/

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Slide 35 Largest Urbanized Areas: Spotfire

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Slide 36 Coastline County Population

http://www.census.gov/dataviz/visualizations/039/

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Slide 37 Coastline County Population: Spotfire

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Slide 38 I-90 Population Density Profile

http://www.census.gov/dataviz/visualizations/031/

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Slide 39 I-90 Population Density Profile: Spotfire

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Slide 40 Keeping Pace With New York

http://www.census.gov/dataviz/visualizations/036/

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Slide 41 Keeping Pace With New York: Spotfire

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Slide 43 Population Shift: Spotfire

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Slide 44 I-10 Population Density Profile

http://www.census.gov/dataviz/visualizations/030/

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Slide 45 I-10 Population Density Profile: Spotfire

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Slide 46 I-5 Population Density Profile

http://www.census.gov/dataviz/visualizations/025/

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Slide 47 I-5 Population Density Profile: Spotfire

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Slide 48 Islands of High Income

http://www.census.gov/dataviz/visualizations/019/

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Slide 49 Islands of High Income: Spotfire

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Slide 52 Following the Frontier Line

http://www.census.gov/dataviz/visualizations/001/

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Slide 53 Following the Frontier Line: Spotfire

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Slide 54 Changing Ranks of States

http://www.census.gov/dataviz/visualizations/023/

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Slide 55 Changing Ranks of States: Spotfire

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Slide 56 Cartograms of State Populations

http://www.census.gov/dataviz/visualizations/021/

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Slide 57 Cartograms of State Populations: Spotfire

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Slide 59 Before and After 1940: Spotfire

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Slide 60 From Physical to Political Geography

http://www.census.gov/dataviz/visualizations/011/

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Slide 61 From Physical to Political Geography: Spotfire

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Slide 62 Differential City Growth Patterns

http://www.census.gov/dataviz/visualizations/016/

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Slide 63 Differential City Growth Patterns: Spotfire

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Slide 64 I-95 Population Density Profile

http://www.census.gov/dataviz/visualizations/012/

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Slide 65 I-95 Population Density Profile: Spotfire

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Slide 66 Increasing Urbanization

http://www.census.gov/dataviz/visualizations/005/

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Slide 67 Increasing Urbanization: Spotfire

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Slide 68 Gaining and Losing Shares

http://www.census.gov/dataviz/visualizations/006/

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Slide 69 Gaining and Losing Shares: Spotfire

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Slide 71 TIGER Shapefiles: Census Bureau

http://www.census.gov/geo/maps-data/...iger-data.html

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Slide 72 List of United States Cities: Wikipedia

http://en.wikipedia.org/wiki/List_of..._by_population

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Slide 73 Albany NY Latitude and Longitude

https://www.google.com/search?q=alba...hrome&ie=UTF-8

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Slide 74 Top 20 Cities: Spotfire

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Slide 75 Conclusions and Recommendations

http://flowsmapper.geo.census.gov/fl...owsmapper.html

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Slide 76 Conclusions and Recommendations: Spotfire

Web Player

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Spotfire Dashboard

For Internet Explorer Users and Those Wanting Full Screen Display Use: Web Player Get Spotfire for iPad App

Error: Embedded data could not be displayed. Use Google Chrome

Research Notes

Census has a team of about 60 creating visualization and will provide contact information and comment opportunities to the Web Site:

http://www.census.gov/dataviz/

Mentioned that Ben Schneiderman was the pioneer and visiting scientist to them in the past. He invented Tree Maps, etc.

Eric Newburger, US Census Bureau 

Better: http://www.zoominfo.com/#!search/pro...rgetid=profile

Minimal: http://www.linkedin.com/pub/eric-newburger/40/587/b83

Alex Tait, International Mapping: http://internationalmapping.com/about

Alex Tait

443-367-0050 x231
alex@internationalmapping.com
International Mapping, Ellicott City, MD

When Google Does Not Provide Latitude and Longitude: http://www.realestate3d.com/gps/latlong.htm

Key Slides

Requirements for a Data Visualization of the Week

1. Four or more dimensions of analysis, whether data or annotative
2. Sufficient annotations to stand alone, without narrative support from any other product
3. All direct statements  in annotations must have passed statistical review
4. Must comply with good visualization practices which present maximum relevant information with minimal cognitive load
5. If multipage, must include a front page that presents an overview
6. If multipage, must include intuitive index
7. If interactive, must include intuitive controls
8. Interactivity code must comply with security and browser standards (e.g. browser independence)
9. Because interactivity – even so simple a thing as animation – comes with a cost in effort and time, interactivity must add value in both understanding and new dimensions of analysis
10. The image should include Census Bureau branding
11. Must comply with 508 rules
12. Must make the dataset behind the visualization available in an excel file (or CSV)

Implications for production process

• No Adobe Flash

• Javascript / HTML / Images
• Learn to love image swapping!
• Simple (or no) interactivity
• Keep focus on good visual ideas not cutting edge interactivity

Data Visualization: Images That Tell a Story

Date: Thursday, March 28, 2013
Presenters: Eric Newburger, US Census Bureau 
Marc Perry, US Census Bureau
Alex Tait, International Mapping

 

Register Now! My Note: Did this.

 

Format: Webinar
Date: Thursday, March 28, 2013
Time: 11:00 AM–12:00 PM ET
Fee: Free
Presenters: Eric Newburger, US Census Bureau 
Marc Perry, US Census Bureau
Alex Tait, International Mapping

Description  

Data Visualization, when done right, will communicate information clearly and effectively through graphics. The Census Bureau's known for their great work creating visual images out of the data they collect and lots of agencies wonder "how do they do it?" Well, here's your chance to find out. Please join the Census Bureau on this webinar to hear their philosophy around data visualization and the internal educational programming they've set up. Also get a walk through of their data visualization creation process and learn about the tools they used.  

What You'll Learn 

During the webinar, you'll learn:

  • Why data visualization is important
  • The steps in a data visualization creation process
  • What tools and resources you need to create graphical images out of data

Who Should Attend

Anyone interested in learning how to create visual representations from data to tell a story. 

About the Presenters

Eric Newburger is the Assistant to the Associate Director of Communications and one of the leads of the Census Bureau's effort to use the power of data visualization to open its data sets to a broader public. For the past 15 years, he has been a statistician with the Census Bureau, publishing on subjects from computer and Internet use to voting to educational attainment.

He has been designing data displays professionally for nearly 30 years, having begun as a teenager in a family business publishing guides to medical services in the Washington, DC, metro area.  

Marc Perry is a Demographer and the Chief of the Population Distribution Branch in the Census Bureau's Population Division and the technical lead for the Bureau's data visualization efforts. He has authored or co-authored numerous publications on topics such as domestic migration, population concentration, and metropolitan areas. He was a coauthor of the Census Atlas of the United States.

Alex Tait is the Chief Cartographer and Vice President of International Mapping in Ellicott City, Maryland. As a contractor with the Population Division, Alex and his team assist in producing the the Data Visualization of the Week. Alex has worked on many projects with the U.S. Census Bureau including the Census Atlas of the United States. He also works on other projects ranging from international boundary litigation to interactive mobile map apps.

Content LeadDigitalGov University 
Page Reviewed/Updated: March 7, 2013

On-Demand Webinar

NOTE: Large files will take more time to download

The Census Bureau’s Data Visualization Mission

Slides

Slide 1 The Census Bureau’s Data Visualization Mission

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Slide 2 Graphic 1 Slave Population

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Slide 3 Graphic 2 Deaths

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Slide 4 Graphic 3 Number of Communicants of the Principal Denominations

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Slide 5 Graphic 4 Telephone Operator

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Slide 6 Graphic 5 Table 86 From Statistical Abstract

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Slide 7 Graphic 6 Table 1 From Statistical Abstract

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Slide 8 Graphic 7 Table 743 From Statistical Abstract

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Slide 9 Satellite Photo 2000 Population Distribution in the United States

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Slide 10 American Fact Finder

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Slide 11 Readings in Information Visulaization Using Vision Book

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Slide 12 The Washingon Post Interactive Graphic

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Slide 13 The New York Times Graphics

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Slide 14 Show Me the Numbers Book

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Slide 15 Creating More Effective Graphics

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Slide 16 Data Visualization Team

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Slide 17 Inside Census Data Visualization

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Slide 18 Census Visualization of the Week

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Slide 19 Requirements for a Data Visualization of the Week

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Slide 20 Islands of High Income 1 Greater Than $18,000

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Slide 21 Islands of High Income 2 Greater Than $70,000

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Slide 22 Islands of High Income 3 Greater Than $32,000

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U.S. Census Bureau Data Visualization of the Week

Slides

Slide 1 Title Slide

AlexTaitSlide1.png

Slide 2 Census Visualization Gallery

http://www.census.gov/dataviz/

AlexTaitSlide2.png

Slide 3 Data Visualization Parameters

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Slide 4 Implications For Production Process

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Slide 5 How Do We Put One Of These Together?

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Slide 6 Concept 1

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Slide 7 Concept 2

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Slide 8 Data Preparation 1

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Slide 9 Data Preparation 2

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Slide 10 Rough Graphics 1

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Slide 11 Rough Graphics 2

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Slide 12 Rough Graphics 3

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Slide 13 Storyboard

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Slide 14 Final Graphics

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Slide 15 Code Development 1

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Slide 16 Code Development 2

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Slide 17 Web Presentation

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Slide 18 Tips for Concept

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Slide 19 Tips for Production

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Slide 20 Tips for Process

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Slide 21 Samples From The Gallery

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Slide 22 Questions?

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Transcript

Source: http://www.howto.gov/sites/default/files/data-visualization-census-transcript_0.txt (TXT)

Event Started: 3/28/2013 3:00:00 PM
----------

Please stand by for realtime captions.

Introduction

>> Hello everyone but we are going to get started in just a minute but I just want to let you know if you are having technical difficulties you can call one 800 263 Hello everyone but we are going to get started in just a minute but I just want to let you know if you are having technical difficulties you can call 1-800-263-6317 and choose option two. The webinar option. Than option one, option one. Thank you and we will get started in 2 min. option one. Thank you and we will get started in 2 min.

>> Hello everyone and welcome to the webinar. I am [ Indiscernible ] the program manager digital of University. And we have a great event planned for today on data visualization.

>> We have invited one of the agency leaders in this field to talk about how turning data into representation can help mitigate that data and provide meaning and understanding at a glance.

>> Let me introduce the presentation of the Census Bureau -- Eric Newberger -- is the assistant -- Eric Newburger  -- he is the assistant to the associate director of communication and one of the leads of the Census Bureau's efforts to use the date hour of data visualization to open its data to a broader public.

>> We also have Mark -- Marc Perry  who is the chief of the relation branch of the Census Bureau's population division. And the technical lead for the bureaus dated the -- date it this relation effort.

>> And finally Alex Tait  is the chief photographer and vice president of international mapping in Maryland. As a contractor with the populations divisions, Alec and his team assist in producing the data visualization of the week.

>> And here is Eric.

Eric Newberger

>> Thank you very much. And thank you very much for having us. We are all three of us excited to be having this discussion.

>> We have the data -- the Census Bureau's data visualization mission. We have the program and the intent is to greet this increase the ratio graphics to text to the Census Bureau publications both online and in print, and to open the databases and analyses to a broader public.

>> How to get to the point where we needed a program to do that?

>> We have -- history of the Census Bureau going back sometime -- the map that you're looking back is from 1861 actually. And is now was one of the first [ Indiscernible ] not ever put out. The Orthodox max that I know of was invented 20 years earlier by some officials. This is the first one that I am aware of that was put out by a government agency.

>> This particular map is the slave population in the southern states. This map actually have a considerable historical importance as you might imagine to the subject matter. But step back from the main -- a moment and consider this was the census bureau and/or almost the sheep are always the first time in the world, we were resenting people -- presenting people as geography. That was not the time.

>> In 1870 to 1890, and even into the early 1900s we were producing atlases that were filled with small multiples that tell people [ Indiscernible ] and that were filled with pages that look like this. Pages that were covered in the presentation of data in a visual way. To open up these dated to a broad audience. And then what happened?

>> Well the [ Indiscernible ] tabulating machine happened. In 1890 for the first of the census had a machine I could do tabulation. Than this machine was a resounding excess in 1880 -- said this. So eight years it took to process the 1880 census took I believe a little over two years -- and we actually did it twice so that we could check the results.

>> Now that idea that we had the chemical aids for tabulation was that led to an explosion in the availability of data from the Census Bureau. Moving into the 20th century. Women to electronic disease -- electronic machines and him actually the large-scale machine that we have in the publications all started to correct this or this.

>> Or this. Because what we have is we are tabulating machines. That was the stated the art -- the state-of-the-art was a well organized well cut table data processed in a way that could be useful provided you are willing to redo the table.

>> And reading through the table was really necessary. We were putting out whole books of tables and for the people, the researchers who could spend the time and had the energy and the know-how to go through those tables -- we were providing data that had never been available before in the United States or most any other nation.

>> And it was a real new. But -- boom Huck

>> But at the same time I was lamenting the audience. It was limiting the audience to people who could see the table with very rare exceptions. We did on occasion put out graphics with -- like what you are looking at now which I think is one of the great graphics of all time because one.is 7500 people. So we're actually seeing the people of the United States come together to make the United States. There is actually not picture of the United States [ Indiscernible ] it is all just data.

>> And so I love this one but it was very rare. Very very few images that you could find especially during the latter half of the 20th century in the Census Bureau public -- publication relative to the number of people the table.

>> And of course the ultimate version is the American factfinder. American factfinder is the data submission tool that the data sent -- census bureau is currently using. Amy not know the applicant is. Is approximately -- at last that I am aware of -- 370 -- at last that I am aware of -- 370 billion table cells inside American factfinder. 370 inside American factfinder. 370 billion. Most of them have [ Indiscernible ] associated with them so you can actually pretty much double that number.

>> Is an enormous data sent. That is the thing -- we are really not talking bout tables anymore. We have gone beyond an analytical table.

>> We are talking about data sets.

>> You have to read through to understand it to make sense of it.

>> We want to open up American factfinder. We want to open up all the tables in the Census Bureau. We want to open up the data set that we have for that broader public by providing visualization that can open up those data sets to people who don't use tables.

>> And even though we have been making improvements for American factfinder that you see on the screen among the indexing improvement that we have been making still -- it still ultimately is about finding your table. Like how do you envision what is in the table.

>> So this is that Schneider -- Schneiderman. Reading -- readings in information visualization. In regards to interactive visualization.

>> Then Schneiderman and is up at the University of Maryland have been instrumental in -- okay -- just if you look at that smart phone in your pocket, a lot of the interactions you are having with it like your sightings to open the screen and other such -- that came out of his lap. That is his work. He invented [ Indiscernible ]. He did a lot of stuff pocky change -- the talk that he came to talk to us at the Census Bureau. Roughly about one a month -- to talk about the work that they're doing. When I tell you that we are 100 years in the Census Bureau, we would just producing tables. We were producing analysts who thought in tables. We were producing analysts who knew how to make tables. Really really good tables. But what we're doing is making tables.

>> To ship to visualization. To open up the data sets for visible -- visualization requires us to change the culture with the building. And that is what the data visualization project Census Bureau is really about.

>> And it starts with bringing in luminaries from the field to talk to us about visualization. What is going on in the world so we can get excited. And learn a little something at the same time.

>> We brought in the panel of -- from the Washington Post. Their graphics people. We brought in someone from the New York Times. We brought in Stephen few. Is a corporate data trainer in Basle edition pocky was but one of our monthly speakers and fill the -- filled the auditorium. But also you say the first couple of days to do the first of our formal trainings in addition to the monthly visits with formal training.

>> Naomi Robbins published creating more effective graphs. This is the guy but to creating graphs. With academic work. And she is our -- one of the core instructors for the ongoing classes that we are doing on the data business.

>> We have other sectors of the people coming in. I don't want to show you a list but I just wanted to give you a sense of the sort of the effort -- is really about the minds of the analysts more than it is about any particular tool or software or anything else.

>> One think everything on the line --

>> We have a data visualization team of which 63 members -- with 4000 people is a huge number but 23 different areas are contributing people.

>> Each one of these -- of these are all these are the prime areas within the Census Bureau and the publication oxo that we have someone or -- someone from everywhere or a couple of people from everywhere. To explain how we can build the auditorium we have the event.

>> Because overly Is a network that extends throughout the building. We have an internal website to support this network.

>> And we also have devastation projects. Of the devastation projects were intended -- intended to provide a prime location on the front page of the website. To give prominence to data Islamization as well as showing the people within our building to take people that existed in a different context and review different -- review different things.

>> Immunities to -- devastation projects as the visualization of the week.

>> How internally we have requirements for the data visualization of the week -- four or more dimensions of the analyzes whether data or an attempted -- annotative -- and there is a list of these and each of these have subheadings and we don't even need to know about all of that.

>> Let's actually go to the picture. Alright. So here is one of the most popular data visualizations that we have. Up until last week -- which I imagine we will come up with something -- this is eyelids of high income. Now the idea here is to just take the ACS meeting household income by county data. -- Median household income by county.

>> And provide a very minimal interaction to see what counties are coming up -- and the interaction is just as later across the bottom of the screen at present the cider is all the way to the left. So any County that has a median household income higher than $18,000 shows up in green. And of course everything shows up in green.

>> But what happens if we move it later over $10,000. Now we understand why it is called islands of high income. Because we see these isolated counties.

>> Or in the Midwest. We see the Northeast four-door as this long stretch of high to medium household income or county. This continued was patterned. Minute islands of much as a a cappella.

>> We see how on the West Coast we see the California and Los Angeles areas -- the Chicago area of the lakes. We see these different areas and we have an understanding now of the wealth distribution in the United States. Which all of these data were previously available in tabular format through American factfinder. You can download that. If you greatest picture -- or you can come to this -- the date of this relation of the we can use the slider and in about 10 seconds get this kind of understanding.

>> And you can go the other way also.

>> Move the slider down again so now you're looking anything is greater than the $2000. Which is pretty low compared to median value of around [ Indiscernible ] thousand.

>> $32,000 or more shows up in green. Which means anybody who is in white is less than $32,000 as a median household income in the County

>> We see a different grouping. A different pattern emerging.

>> To this one simple interaction, this one -- pretty much the simplest possible interaction you can have, turns what was a data set that was a table of 3141 colonies -- and it turned that table into an understandable analytical tool that really does open up the data set to a wide public.

>> So that's what we want to do -- that's what we want visualization to doing this: what actually all of our Islamization to do is used to strive to become

>> And this one doesn't.

>> Enough to introduce the person who created this visualization I would like to introduce Marc Perry  who is my partner and data visualization here at the Census Bureau.

Marc Perry

>> Great, thank you Eric. This is Mark. So I just wanted to let everyone know about some upcoming enhancements in the functionality of the visualization of the week that we will be rolling out over the next probably 3 to 5 weeks or so

>> So for people who have been familiar with the visualization of the week Gallery -- certainly one of the things that you have noticed is we have not really made it easy as of now for people to contact us -- there is in fact no phone number, no dedicated e-mail address -- no common feature -- there's really no easy way for the general public to communicate with us about a particular visualization.

>> And a people have based on their own creative ways -- people know somebody at the Census Bureau and say hey -- can you get this message to the folks who did this.

>> Well we're entertained all that.

>> To the coming weeks we will be adding some nationality. We will be adding a comment feature for each visualization. So you will be able to -- there will be a little icon on the top right corner of the visualization. You will be able to click that to provide any comments or feedback.

>> There will be a little thumbs-up/thumbs down rating. For each visualization that you will be able to use. And also have a dedicated e-mail address. So if you have suggestions on future topics, if you have questions or need clarification.

>> We will finally be making it easier for people to communicate directly with us. So if you have questions about how do you do this, or where is the data set or really any communications of any kind, we will essentially just be making it a lot easier for that to happen.

>> So now I would just turn things over to Alex and he can talk about the details and sort of how we make all this happen.

Alex Tait

>> Alex, go ahead.

>> We cannot hear you Alex.

>>[ Pause ]

>> Alex -- I think you unmuted box Mac Alex, on your audio control panel, unmute your microphone.

>>[ Pause ]

>> Can you hear me now ask --?

>> We can

>> Sorry about that Oaks. -- Folks.

>> My name is Alex Tait and I work at a company got international mapping. And we are a contractor  with the US Census Bureau and we have been working with Eric and with Mark on the data visible addition of the week. And I'm here to show you a little bit about the nuts and bolts about how we have put together these data visualizations together.

>> These data visualizations are in the gallery that Mark was talking about. Here is the web link if anybody wants to go and play with some while I am talking. And I urge you to do so.

>> Before I get into the how-to, I wanted to talk a little bit about the parameters within what we are working for this visualization.

>> We are of course working with the Census Bureau data. And as Eric was pointing out we are dealing with these visualizations for the general audience. The ideal is to show people of the United States with the sense data looks like and how they can see different patterns.

>> We limit ourselves to a canvas item about 880 eight 80 x 6 60 pixels. And these last two are very important -- we wanted the data visitations to be compatible with as many browsers and as many platforms as possible. So these website based visualizations are compatible back to Internet Explorer seven and they are fully compatible with Apple IOS devices. And of course anybody who has been working in digital media knows that that has some implications such as the fact that there is going to be no Adobe flash. Which means we are doing primarily our interactivity with JavaScript and HTML and lots of images.

>> We had to learn to love images -- so there is a lot of the interactivity that you can see that looks like animation is actually very quick image swapping talk -- and a lot of the interactivity is fairly simple. As Eric pointed out we are going for simple and effective on the interactivity so that we have cross-platform compatibility.

>> So this all serves to keep the focus on good visual ideas and not cutting-edge interactivity or animation.

>> So how do we put one of these together? We are going to take a look at the blooming state visualization and I am going to discuss seven stages of the process. And talk about the tools that we use to accomplish each of these stages.

>> Let's take a quick look at the booming sates visualization. I will go to my browser and scroll down to blooming states. And you can see a map of the United States with these sort of what we call the -- we call this blooming stage because we believe like flowers. But each of the circular graphs is representing population change. In each decade from 1790 until 2000 for that state.

>> So if we take a quick look at New Jersey, you can see that the radio rafts starts at 12 clock in the 1790s. And goes around for each of the decades old weight to the 2000. At around 11 o'clock.

>> And we can see -- all the way to the 2000.

>> The populist change has been a positive change because the warm colors have been the population changes -- so there's been a decrease in the population. You can see how fast the jersey has grown. Is growing faster than 18 1830s and 1840s -- and then there has been a gradual slower rate of change.

>> So loudly with something like this together? The first eight -- so how do we put something like this together?

>> First subject the concept. How do we put this -- the tools here are putting together your thinking and your brainstorming and starting out with either questions about data, or data set that you want to look at and try to develop questions out of.

>> I had tossed into the mix the idea of bringing images so you have some idea that maybe you want to show up with a graphic, you are to show it with a map. Pencil and paper come in handy. Voices -- is generally a group to be involved in putting together a concept. And important to have a discussion. And so we have the previous data visualization that we worked on, but also the experience of a demographer or Jennifer in looking at the data.

>> So the question we had for blooming state is what does decade to decade change in population look like for all the states. And here's a quick visualization -- of course I am in the concept stage but I have already shown a rough wrap if you want to take a quick look at some the population changes by decade for all the different states.

>> And this is one quick look at it.

>> So I will be looking at the stages but of course socially early on in the project -- process, your concept stage is David Miller -- motivation stage in the rough graphic stages all intermingle as you trying to figure out the best way to show what you want to show.

>> So we refine the question down to how to wish a regional differences in state population growth?

>> What I'm calling stage II and again the stages do intermingle with the data preparation our primary tools are Microsoft Excel and ArcGIS for databases.

>> So many of you know that this is a wonderful tool for manipulative data. And has many good tools for is alleging data in reference format.

>> Those of the primary tools.

>> This second site about data shows that in the background you can see the raw numbers of population. We then manipulated the raw numbers to look at the percentage of change. So you can see that for New York in 1790, there was a 73 -- in 1790s that is -- from 17 9217 from 1792 1700 -- there was a 73% increase.

>> Third stage will be the rough graphics -- the primary tools here is a sad -- micro soft Excel is very useful. ArcGIS For preliminary mapping. And this is where we bring in Adobe Illustrator to do the graphic thinking -- is a canvas for us to using graphic taking. So often we are using elements out of Excel and ArcGIS and bringing them into Adobe Illustrator.

>> In looking at decade-old population change for each state, we wanted to take a look both at the percent of maximum population, and at the percentage change. You can see that for most states and certainly for Iowa, there is a radical visual difference between these two ways of looking at the data.

>> So for Iowa on the left, you're looking at in each decade how much of a percent of the maximum population, which for Iowa was in 2010, was the population [ Indiscernible ] [ Indiscernible - low volume ]

>> You can see that I have again published very quickly. And each near maximum population as he reached maximum population very early on.

>> The percentage change graph shows that in a different way. So that you can see the radical percentage change in about 1840 when Iowa first started growing.

>> So we have to make a decision and further refined the question and what we agreed to do the data we decided we wanted to take a look at the percentage change.

>> That brings up how that would want to show it. And we thought let's get people thinking a little bit differently. And take that our graph and wrap around a circle so that we will be able to start looking at the data in a different way. And you can see here the transformation from a regular bar graph to a radial bar graph. Anything for you appreciate more help that changes your way of looking at the data, is when you see it in looking at the entire United States.

>> So even in thumbnail format here for the storyboard but you can see that the flowers in the Midwest look very different from the flowers in the West

>> Or in the Northeast. That is a regional pattern that we wanted to show.

>> So stage IV storyboard -- this is very important for the interactivity thinking about the interactivity -- we just lay out a simple series of -- thumbnails to show what would happen if the user is manipulating this data visualization.

>> In this case is a simple mouse over -- one of the -- you have an initial map. You have a mouse over one of the states. Any pop that it pops up a detailed graph. And this allows you to see both at a national level and then at a state level, different layers of detail about the data set.

>> So once we have established the storyboard, and once we have established the way that we will show the data come in that we are able to move on to the final graphics -- in Adobe Illustrator and Adobe Photoshop and we have primary put images for quickly loading. And you can see some of the images that we use for one of the states here.

>> And then we move on to the prodevelopment -- codevelopment stage. Primary tools here where the Adobe Dreamweaver or you one you the way of coding JavaScript in HTML. An excellent appointment that we use the Adobe extended script toolkit to do some special work in Adobe Illustrator. Where we created our -- our developer created a way of generating the circular bar graphs -- the radio or graphs automatically from a data set.

>> Which I hand it would have been very difficult. In the show some of the crowd -- code that he created for some of the radio bar graph.

>> Programmers are quite useful for writing shortcuts for production

>> And then lastly, the web presentation is putting everything together. Using Dreamweaver and other tools for putting together HTML pages. And part of that process is testing in the standard browsers. The explores -- Internet Explorer, Safari Firefox and chrome. So some of these get you mingled, especially in the early stages

>> I thought it would be useful to highlight some of the tips that we have learned. In working with Eric and Mark and working with a programmer and the other folks at senses that are involved in this project.

>> From a concept side of things, as a mentioned it is very important to discuss the concept out loud with others. And I would say that it is a porn to note that those people on your team, but also people not under team. People that are not directly involved. We have got a lot of good ideas on feedback from friends and family. So I encourage you in coming up with concepts, to discuss these things with people who are not necessarily experts in demography or in data visualization.

>> Gather lots of visual ideas -- and we discussed the ways of looking at things. Include your developer and programmer in the early stages. Oftentimes the developer is only brought it at the end after things have been thought through. And people that know how to code and know how to put together interactive elements are very useful to have at all stages of the process.

>> And lastly, shortcuts -- don't shortcut to brainstorming. You to generate a lot of ideas because as I will note later they will not all be the best ideas so you need a lot.

>> Underproduction -- note that it is very easy to copy and paste from Excel to illustrator. So if you are good at visualization -- this was by seeing graph -- if you're good at visualizing, you cannot just copy of the state graph from Excel to illustrator. You can create simple graphs directly in illustrator that I live. Connected to data sets. Encourage your developer to create a library of widgets. Agency as you look through the gallery that there are certain interactive elements that are used on multiple pieces. And that saves a lot of the time when you are looking -- coming up with data visualization -- every week and the clock is ticking

>> Lastly -- be careful. Don't review digital projects by -- products by printing them out. It is important to review digital products in the media by which they are intended to have a better sense of color and type size and graphics effects.

>> Lastly it's about process. Be sure you have an iterative creative process. We work closely with Mark and Eric to make sure that there is multiple pages of review. You need to be able to revise you need to have a lot of people looking at things so that you get good ideas about how to improve both the interactivity if there is some, and the visual oppression of your graphics.

>> And lastly, generate lots of visual ideas because you should probably kill at least half of them. We have a virtual floor littered with dead ideas that start off as something that was promising and we probably found a better way to do it but there were probably three or four ways that did not work well.

>> Alright -- enough about the process. I would like to show you a couple three samples from the gallery.

>> So wickedly blooming states. And I will score down to the very first data visitation that we created.

>> This one is called top 20 cities. And it is a word map, a literal word map. With the names of cities -- are generally in the correct geographic location. And they show how many of the senses decades from 1790s two 2010 -- have a time that city was in the top 20 state

>> And so you can see the large East Coast cities -- Washington and Baltimore, Bill Duffy, New York and Boston -- they have always been in the top 20. So if you take a look at Baltimore and you can pop up a graph and you see its position in the top 20 is ranked fifth up to second, down to 17. But always in the top 20.

>> Bus people don't know that Baltimore was the second-largest city in the US for three decades.

>> We can take a look at New York. Number one.

>> We can take a look at New York. Number 14 every census ever from 1792 2010.

>> Now an unusual pattern that you see here is the city like Los Angeles that many people consider a very important city but of course it is smaller on the map because it only contains one of the 20 -- largest in 2010.

>> You start seeing a different pattern -- and this is a historical pattern that you're looking at. Touched a contemporary pattern. So another level of looking at the data.

>> One of our popular data visualizations, was when we created initially in print. And that you need to take this data and show it interactively in the data visualization for the website. So we were looking at population density along interstate Interstate 95.

>> And we wanted to sort of tend you're in a car driving along Interstate 95 -- have been so the population. And as Eric has said this sort of data is available on the track level or county level on tables for the Census Bureau. But it has been sort of were difficult to look at and essentially more difficult to look at in table form when you're thinking about a profile along the road.

>> So I will go ahead and play this. And you can see as the car travels up I-95, you could see the major cities. There is the megalopolis from Washington to Boston and you can see the cities along I-95 as increases in population density.

>> Again for those of you looking at the technical side of this come up this is a very quick image dropping out and not a true information. And this works in Internet Explorer seven in machines just fine.

>> I'm going to return to the gallery and show you one final data visualization. This is one that came out a week ago. And I think this is the most popular one to date. And who have not had a chance to play this game I certainly urge you to do it. This looks very much like the March madness brackets that you would probably fill out in your office pool. But in this case, we have substituted the team with metro areas. And we have matched up -- very different metro areas in the United States. And your goal of the game is to pick which one is greater. So I have Portland and Buffalo here. And I will guess that Buffalo and Portland -- [ Indiscernible ] so when I find I wrong come up or Louisiana Buffalo is a red. I have Rochester and Bakersfield. I get that one right, it turns green.

>> And you can see of course that some of them are easy and some are hard.

>> And so Los Angeles goes all the way up.

>> This was a way to connect both the popular culture phenomenon and also this was timed for the release of the new estimates for the metro area population.

>> It was way to tie senses point -- Census Bureau even to popular culture even to put into debarment that did very well with people commenting on it. And we were written up in the Hartford current as the lovable nerds at the Census Bureau.

>> So that's it for my presentation and I will pass it back to the webinar coordinator's.

>> Thank you Eric, Mark and Alex. We're going to take questions. But before we do on the digit is a special guest, Jean Holmes -- is the digit to go -- specialist. And just talking about the communities, open visualization.

Jean Holmes

>> Thank you so much.

>> I am coming through?

>> Yes.

>> Great.

>> Will like you guys to know about data.gov is that we have a lot of visualization capabilities. As well as 365,000 geospatial data sets.

>> The data.gov is an open government initiative from the US office of [ Indiscernible ]. And we provide access to over 400,000 data sets from 185 different federal agencies.

>> We also go beyond the federal agencies to cities, states and counties. As well as international partners like the United Nations and [ Indiscernible ]

>> You can finalize the data there and you're able to do a variety of positions on it.

>> So the old Geo spatial -- topics in

>> -- Is actually partial now at the deck of.

>> You can do mapping, visualization. You can also do visitation a little bit as Alex was talking about -- you can make charts. And interact with maps. Looking at matching up different kinds of data sets together from different agencies. Said Mac also on data.gov we have a variety of community. These are topical areas international ours interests -- they range from things like energy and education to business an infection ring out and some of these communities are very visually focused with data focused.

>> The oceans community for example focuses entirely on coastal and Marine special planners. So these are folks are really looking at mapping data and to look at the addictive analysis. And the use of coastal areas and around the lakes.

>> So there are a variety of resources -- that we have a data.gov and access a lot of different data. So we would love to have you guys come in and join the community. Look at the data and create visualization that you can venture backed. To the public. Suggests new data sets that you would like to have access to the federal government. And we will work her to make this data sets available to you.

>> Great. Thank you so much Jean.

Questions and Answers

>> So let's jump into the Q&A. I have a few questions here. And Eric I think we go to you. About by the weight accessibility. To talk a little bit about what kind of process to go through to make sure that the data visitations are -- that meet by the late -- law and also one attendee engine that of course there is [ Indiscernible ] but what else could folks do to make sure that the graphics made by the lead standard.

Section 508 Accessibility

>> There are -- okay there are three things you have to know. And if you're asking the question you may already know some of that. What everybody knows that color choices. Colorblindness is not actually colorblindness -- you're not blind to color -- their particular fields of color that you don't see. And their different ones depending on the particular type of impairment.

>> So choosing the color palette which has a lot of contrast. But does not dazzle your eye if you have normal vision that is sort of high analyst. Now there are services that we have been looking into that will actually -- that are online of their free. And you can actually submit your visualization to these services and they will send you back what it looks like to someone who has a particular type of color impairment.

>> And that could be helpful. But just picking a regular color palette that is very very handy.

>> One of the part about 508 compliance sexually the interactivity itself. Write properly speaking, ultimately you should be able to do things with your keyboard instead of the mouse. Because they're people that cannot use a mouse.

>> That is part of 508 compliance. And that's the one that most of the think about. If you can have keyboard controls in addition to the house, that helps a lot.

>> And the last thing is -- and Mrs. the big fallback position.

>> Is -- and this is true for all of the Viz-of-the-Week and productivity us want to do. The data needs to be  available in the tabular format that is machine readable. And you need to be able to contact from the visualization. So if someone says I can't see this visualization, I have no ability to work with it.

>> The data need to be available in just a regular table. So the table behind the visualization needs to be available with one click. And it needs to be available in one of the standard formats that the machine reader could read. So theoretically someone could say -- have a listening device or a machine reading device that they could listen to that would read out: title, road title -- etc.

>> And those are the three things to know about Bible week plan Phillies are my perspective. Mark or Alex if they want to jump in and would be happy to hear them.

>> [ Indiscernible - multiple speakers ]

>> I think you hit it just right.

Census Flows Mapper

>> Okay great. The next question -- the census flow maps as a uses flash -- is used as exception to what you mentioned Alex about using image swapping?

>> There are a few exceptions. And to gain additional interactivity, there are a few exceptions.

>> In general we try to make sure that everything is really cross-platform but that was one case where to get the additional interactivity, the flash environment was limited.

>> Okay great. And can you identify what kind of files that you use to export from the [ Indiscernible ] to take into illustrator.

>> Sure. So sometimes we are coming out of ArcGIS straight to JP or JP e.g. files and actually skip the Adobe Illustrator and take those images right into Photoshop. But if we are going into Adobe Illustrator, there is an export as adobe illustrator format.

>> To come out of our -- to come out of -- so if you come out with another component out of a RC map ArcGIS or -- you can come out of that

>> One of the key things to do is make sure the resolution on the export is very high. That to 1200 or maybe 24 under -- so that you get a level of detail that will produce a satisfactory graphic image.

>> Okay great. Specifically on the radio charts, is any convention about what point should be at the total cost position -- the 12 o'clock position?

>> I think the convention to follow is that the start point that you want people to initial -- to start the readings of the chart is at 12 o'clock.

>> So we wanted people to start reading at 1790, so we put that 12 clock. And people will generally read a radial chart as they would read a clock. So going from 12 clock to one o'clock to two o'clock and three and four and around clockwise.

>> And that is I think the -- was in a rule of thumb I think -- we're thinking people that expected people to work really hard if they were doing anything but starting at 12 clock going clockwise.

>> And I would like to point out that working hard is not what we are after your.

>> It is sort of the opposite of what you're after.

>> That is exactly right. You want -- what we like about the radio graphic is that people can related to a clock and read it that way. So you absolutely want to make weedy things as easy as possible. There is sort of a balance between getting people to look at things in a new way, but still keeping it easy to read and understand me.

>> Going along with that answer, do you run the graphics [ Indiscernible ] is to see if they can get that at a glance type of understanding from what you have created?

>> Yes -- this is Alex about -- this is Alex. Absolutely. Is important to get your friends and family involved at the concert stage without -- especially a big usability stage once you have created something in your testing it.

>> We have a team that is putting things together initially. 18,000 people from international mapping and people at the Census Bureau. And then it goes around the Census Bureau and people chime in. But those folks at Census Bureau are pretty much the graphic and data experts. So we went to to people outside of demography and data that will take a look at it.

>> And we try to do that on every graphic.

>> This is Eric again.

>> Also for visualizations that are really interactive tools more than visitation -- there are so more complex data sets that weird explaining visually at this time. And those tools go through formal usability testing where we have taken people from the public and down in front of a machine and asked them to do stuff. And -- we formalize -- when it gets to a tool that will exist for love, the web. And it will have a lot of viewers with a broad push knowledge -- with a broad data set -- we make these in a formal usability testing.

>> Great -- that was another question. Thank you for addressing that.

>> Also, you talk little bit about the time it specifically takes to run through that seven step process?

>> Of course. As you might imagine it is quite variable. And some start with a very good idea and we know how we want to visualize it. And we are using a widget that we have already created in every thing can be done in a day.

>> I say that is unusual. It usually is a process of a couple of days. Time spread over the weaker to. We are working on a weekly schedule. So we have to have many things in the pipeline.

>> We don't always work on them from start to finish. We have several in process.

>> I would say that the range is from half a day to day up to several days.

>> And this is Eric again I would like to add in that Alex takes that long up because Alex does this for a living rock as we move -- as a -- Alex does this for a living.

>> Your results may vary. As we move to people having people inside the building, we are giving them a bit more time.

>> Okay great.

Values of a Visualization

>> K talk a little bit -- about the consideration that is given to these values of a visualization -- versus a simple -- and I'm quitting -- quoting here -- for several does anyone ask the question who cares about the density of population along I-95?

>>[ Indiscernible - multiple speakers ]

>> Go-ahead Mark. Now I will just buy another point here so some of the early visualizations -- you will notice if you look at the gallery, probably the first two dozen were heavily historical data and almost entirely, if not entirely from the census.
>> And there's a reason for that because we were essentially leveraging some work that we are even doing. For a different effort.
>> So those visualizations are ones which we had -- which we basically had already drafted many of them. And if you kind of look at the later ones that we are now branching out into other data sets we have things that in some cases are not so historically minded. So big wreck technology and rosacea last week. That assist the most recent estimate. There's nothing really historical about that one.

>> And they definitely very week by week. In terms of the wow factor. I think there is -- very different reasons and different values for each one. Some of them you know they really do maybe spark an interest to get people to them -- to that look at data for other things. Saw them like the one Eric showed with the eyelids and high income -- you really I mean you can get an awful lot of that visualization. I don't know whether you would actually need to to consult any of these tabular data behind it. Because it is essentially all there just in a different form.

>> So it basically buries. But certainly they -- we want there to always be substance behind them. This not just sort of a wow factor.

>> And I would like to chime in. That I don't understand the question about who would be interested in the population density along any major roadway. That question does not make sense to me. I work at the Census Bureau. I care a lot about population density. And they don't understand if you don't.

>> [ laughter ]

Makeup of Team

>> Thank you. We have a couple questions about the makeup of your team sheet so I am going to just try to lump them together. So here we go. What advice would you have for someone looking to break into this field -- what tools or programming linkages would you suggest them mastering. And I would come to these make up your team?

>> Okay -- I will start that one [ Indiscernible - multiple speakers ]

>> I know Eric will have a lot of good answers. But the first and foremost -- now your data. The first competency is to note your data and not the analyses and to be able to think about what does data mean.

>> That is -- if it is first, last, middle -- you have got to have that. And a big mistake that I can -- one of the things we have to fight here is people who are sort of excited about learning programming or learning the incredibly necessary work of development. But don't really know -- they have a look at the data. I mean they sort of trust that if they learn programming, then everything else will flow from it. But it is backwards. So before we talk about all of the necessary [ Indiscernible ] I want to pitch in that you have to start with that one

>> I think that is a great way to start Eric. And I would argue that every member of the team -- even if they are not specialists in the data set or in the subject matter of the data set, needs to take the time to understand that at least the basics about publishing data. About canonic data. So that they can better do their role, perform their role in the team.

>> And I think the team would start with a data expert. And this is somebody that is not just good with numbers, but good with the subject matter of the numbers. That can be one person or possibly two people.

>> You need somebody who is a very skilled in graphic arts.

>> Sort of before the programmer, I would but the people that can visualize data and graphic ideas into effect using graphic arts software.

>> If you can't make the data visual, that is the next step after understanding the data -- is making the data jewel.

>> And a simple non-interactive image is often the best way to share the data or a very effective way. So before you get to the programming, you have to create the graphic images.

>> So you need someone who understands the data. And you need someone to make a visual -- often a greater -- graphic artist. And you need a programmer or two that understands the interactivity and can write the code.

>> That sometimes this would be to people -- what would be the interface -- user interface specialist and one that can write the code that makes things happen.

>> Sometimes one person can do both of those roles.

>> So you have got for five people on the team. And specifically to the question of what software to use -- I sort of laid out some of the software, but very specifically to a programming language. I would say the programming thing which to learn is JavaScript. All the interactivity that we have created, with the exceptions of a couple of flash's limitations, is all done through JavaScript.

>> Anything to add Mark?

>> I will echo what Eric started by saying if you don't understand the data, then you don't know whether it is something -- okay is it something that you want to map? Is it something that you want to graph? Isn't something where the story is stored gold -- is it something where the story is historical?

>> The data will tell you all of those things. And if you don't know the range of the values, it is really hard to kind of get past that. I don't know how you can -- maybe you can look out. But if you don't have somebody who really knows the basic stories, it is hard to get past that. Maybe they don't know anything else. Maybe they're not good at the visualization part or the programming or anything else. But they can at least tell you in no -- these are the three or four important things to know about this.

>> And we sometimes don't -- we don't like to use the word stories but in fact that it can but they are a little bit. What are the findings what are the three or four -- if you are looking at say -- County level income data as you would've the three or four things that you want to be with to say about the data set?

>> And so if you have the person in the room knows that, everything else is really just edit the details.

>> And it can be hard. Definitely at census we need more people who come to have a visual skills. But you start the data set knowledge and everything goes from there.

>> Great. Thank you all. I just have one more question because we are getting close to the time to wrap up. But can you each tell us outside of your own work I'm a what are some of your favorite pieces of data visualization.

Favorire Visualization Sites

>> Okay well I can start by just talking about various websites I think are worth checking out and keeping an ion to see what they are doing because they have good visual station -- data visualization practices. And great post -- practitioners. So certainly Eric mentioned the New York Times. I would certainly visit their website and a regular basis and check out the data visualizations that they produce. They have some very good work. Especially in rats -- and interactive graphs.

>> Another newspaper site is the Guardian and the United Kingdom. They have sort of a data visualization lab. I think is under their That just as data.

>> So those are two really good websites to check on a regular basis for data digitization.

>> Alex -- you stole my site. First and foremost I was going to say the New York Times. I can't think of any other sort of major was offhand. I think great data visualizations all over the West -- I mean so much more than even really two or three years ago it seems to me. Maybe I am more sensitive to it now because I working closer to it. But it just seems like there is -- there are just lots lots more great examples out there of things to kind of inspire us. And you might see something that works really great for one use, and you can just take it and repurpose it for another.

>> Forbes magazine had a great interactive website a couple of years ago. On migration. That you know you could use that same thing for commuting data or for commodities data or other stuff.

>> And as for me, okay -- I still think the census bureau atlases from the 1800s were really just tops. But that's because I am very fond of [ Indiscernible ].

>> There are a few Google the elements -- just the phrase in the elements -- and you click on images F you are doing an image search. And you come up with a couple of data digitization. One of which shows the stability of the elements. And it is a simple -- ages shows stable systems -- protons versus neutrons -- and provides a color-coded to show how stable the particular element is or the particular formation.

>> And then it shows the one-to-one line. And the one-to-one line -- the scatter plots diverts from it. So that's the bigger the Adam at the bigger element, the more neutrons you need to achieve stability.

>> I consider this to be the visualization -- [ Indiscernible ] in the entire universe because it describes the entire universe. It actually -- the nature of matter. And you can just see -- is neutrons -- that were stability from an Adam comes from. The whole thing derives from a simple scatter form -- I am completely astonished by that. So that is my favorite visualization from all-time except possibly for the Census BureauGovernor  that I showed you. Where the people of the United States come forward to actually form the United States.

>> So those are favorites

>> Great. Thank you so much. I would like to thank everyone for attending today. And if your question was not answered, we would do our best to follow up with the Census Bureau and get back to you.

Conclusion

>> Again, let me thank Eric, Mark and Alex. Thank you so much for joining us and taking time to present on this topic today.

>> And thank you to Jean Holmes for your brief introduction and reminder on data.gov and what it has to offer.

>> That is the end of our webinar. Thank you all.

>> You're welcome.

>> [ Event concluded ]

Marc J. Perry Chief, Population Distribution Branch

Source: http://www.census.gov/newsroom/relea...perry_bio.html

Marc Perry is a demographer and chief of the Population Distribution Branch in the Census Bureau's Population Division. He has authored or co-authored numerous publications on topics such as population growth patterns, domestic migration, population concentration, municipal annexation, and metropolitan areas. He was a co-author of the Census Atlas of the United States, for which he received a Silver Medal Award from the Department of Commerce. He has also received Bronze Medal Awards for work on the 2010 Census congressional apportionment, the 2012 release of 1940 Census records, and the standards for delineating metropolitan and micropolitan statistical areas.

Perry received his master's in sociology from the University of Wisconsin-Madison, with a focus on small area population estimation. He also received a bachelor's degree in sociology and economics from the University of Massachusetts-Amherst.

Population Change in U.S. Counties and Metro Areas, Marc Perry, U.S. Census Bureau

Source: http://www.census.gov/newsroom/cspan/pop_change/

My Note: Why not do this the way I do with MindTouch and Spotfire?

Friday, March 22, 2013 at 9 a.m. EDT

Marc Perry, chief of the Population Distribution Branch at the U.S. Census Bureau, discusses statistics about population estimates and components of change for the nation's counties and metro areas since the 2010 Census.

View the archived segment Link to a non-federal Web site

Biography: Marc Perry My Note: See Above

PRESENTATION [PDF]

Slide 1
Slide 1:
Recent Population Trends for counties and Metro/Micro Areas[PDF]
Slide 2
Slide 2:
Highlights, 2011-2012[PDF]
Slide 3
Slide 3:
Percent Change in Population by County [PDF]
Slide 4
Slide 4:
Percent Change in Population by County: 2011 to 2012 [PDF]
Slide 5
Slide 5: 
Percent Change in Population by County: 2001 to 2002 [PDF]
Slide 6
Slide 6: 
Percent Change in Population by County Size Category: 2011 to 2012[PDF]
Slide 7
Slide 7: 
The 10 Fastest Growing Counties: 2011 to 2012[PDF]
Slide 8
Slide 8: 
Numeric Change in Population by County: 2011 to 2012 [PDF]
Slide 9
Slide 9: 
Metro and Micro Areas[PDF]
Slide 10
Slide 10: 

Percent Change in Metro and Micro Area Population: 2011 to 2012 [PDF]
Slide 11
Slide 11: 
Percent Change in Counties Outside Metro and Micro Areas: 2011 to 2012 [PDF]
Slide 12
Slide 12: 
The 10 Fastest Growing Metro Areas: 2011 to 2012 [PDF]
Slide 13
Slide 13: 
Natural Increase (Births Minus Deaths) for Metro and Micro Areas: 2011 to 2012 [PDF]
Slide 14
Slide 14: 
Net Migration for Metro and Micro Areas: 2011 to 2012[PDF]
 

Sources of Information:

News Release: Oil and Gas Boom Driving Population Growth in the Great Plains, Census Bureau Estimates Show 
Press Kit: 2012 County/Metro Population Estimates My Note: See Below

Additional Information:
Population Estimates main page

Data Visualization Gallery

Source: http://www.census.gov/dataviz/

A weekly exploration of Census data. 

The Census Bureau is working to increase our use of visualization in making data available to the public, and this gallery is an early part of that effort. The first posted visualizations will pertain largely to historical population data, building on prior work done to portray historical changes in the growth and redistribution of the U.S. population. For later visualizations, the topics will expand beyond decennial census data to include the full breadth of Census Bureau data sets and subject areas, from household and family dynamics, to migration and geographic mobility, to economic indicators.

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