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Workflow for the National Geographic World Atlas Mobile App

Workflow for the National Geographic World Atlas Mobile App

Rosemary Wardley, National Geographic Maps
Steve Gifford, Mousebird Mobile

Nathaniel V. KELSO

October 16, 2015

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  1. Data Processing Workflow for the National Geographic World Atlas Mobile

    App Rosemary Wardley Steve Gifford
  2. Introduction World Atlas App Previous versions & Problems Goals for

    new app Data production Data processing Conclusions
  3. World Atlas App for iPhone/iPad Digital & Interactive Atlas Political

    basemaps Flags & Facts Search Index Statistical Overlays Distance Calculator
  4. How  it  was  done  before

  5. How  it  was  done  before

  6. How  it  was  done  before

  7. How  it  was  done  before

  8. How  it  was  done  before

  9. App  Design/UX  Flaws

  10. App  Design/UX  Flaws

  11. App  Design/UX  Flaws

  12. Goals  for  World  Atlas  v.4 Tighter  control  over  the  data

     for  editorial  purposes   Leverage  more  of  our  databases   Reduce  the  amount  of  custom  processing   Fit  into  evolving  Editorial/Production  workflow   App  data  that  is  easier  to  update  &  replicate   Maintain  NG  brand  identity     Add  flexibility  &  reduce  size  of  the  App   Hybrid  Raster  &  Vector  process
  13. Full  Workflow

  14. Data  Production

  15. Inputs:  Standard  Carto  Datasets 75  Million   Zooms  0-­‐2 40

     Million   Zooms  2-­‐4 20  Million   Zooms  5-­‐6 10  Million   Zooms  7-­‐8
  16. Editorial  &  Production  Steps

  17. GFID  match

  18. Flags  &  Facts

  19. Search  Index  Creation

  20. GIS  Database  Steps

  21. Final  Product

  22. Raster  &  Vector  Outputs Background   Raster Full  PDF Symbol

      Shapefiles Boundary   Shapefiles
  23. Data  Processing

  24. Why Vectors? Image Artifacts Blurry text & symbols Tile edge

    discontinuities Size Images are big Vectors are small Selection Data Tapping logic simpler
  25. Vector Processing Symbols Points from GIS database Both visual and

    selection Text Extracted from PDF Purely visual Boundaries Areals from GIS database Invisible, just for selection
  26. Background Raster Including Roads, Rivers Fills, stipples Etc (lots of

    etc) Excluding Symbols Text
  27. Text Extraction Parse the PDF Need for each character Location

    Rotation Size Font Output to Shapefile
  28. Uploading to Mapbox Images basemaps Low res everything High res

    blanks Vectors Symbols Text Boundaries
  29. Anatomy of a Tile

  30. How did it go? App is released and working Text

    is Sharp Symbols are Sharp Data size is way down Old app: 500MB per layer New app:75MB per layer
  31. Conclusions:  Data  Update  Process

  32. Conclusions:  Software  Used Mapbox Studio

  33. None
  34. Wrapup & Contact Rosemary Wardley [email protected] nationalgeographic.com Steve Gifford [email protected]