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MongoDB World 2018: How a Data-Driven Methodology can Influence Aviation Decisions

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Speaker: Annie Wen, Associate Process and Analysis Officer, International Civil Aviation Organisation

Published in: Technology
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MongoDB World 2018: How a Data-Driven Methodology can Influence Aviation Decisions

  1. 1. Annie Wen Integrated Aviation Analysis International Civil Aviation Organization How a Data-Driven Methodology Can Influence Aviation Decisions MongoDB World 2018
  2. 2. Overview • ICAO, UN SDGs & “No Country Left Behind” • Aviation Data-Driven Decision Making • Deep Dive into Data • Apps and Visualizations
  3. 3. ICAO • Specialized UN agency for aviation • Strategic objectives in – safety – capacity and efficiency – security and facilitation, – economic development and – environmental protection
  4. 4. UN SDGs https://www.icao.int/about-icao/aviation-development/Pages/SDG.aspx
  5. 5. “No Country Left Behind”
  6. 6. Aviation Data-Driven Decision Making Evaluate Prioritize Identify
  7. 7. Aviation Safety Implementation Assistance Partnership (ASIAP)
  8. 8. Deep Dive into Data Question: Which States are the least connected to the aviation network and are the best candidates for assistance?
  9. 9. SDG INDICATOR 9.1.1 Proportion of the rural population who live within 2km of an all- season road Photo Credit: Peter Gostelow
  10. 10. Deep Dive into Data
  11. 11. Deep Dive into Data
  12. 12. Deep Dive into Data 360 * 60 * 2 180*60*2
  13. 13. Deep Dive into Data • 183 million squares after disregarding the zeros (no population) • Square  Point Coordinates
  14. 14. Deep Dive into Data • Translated each point and population into JSON • Insert in MongoDB • 183 million documents • Add index on point
  15. 15. Deep Dive into Data In theory, for each airport in the world:
  16. 16. Deep Dive into Data • What happens when multiple airports are within 100 km of each other? – Same person can be counted twice • Does the sum = # people within 100 km of airport in a State? – No, we can’t do 𝑎𝑖𝑟𝑝𝑜𝑟𝑡 𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑆𝑡𝑎𝑡𝑒 𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 – This sum is sometimes more than the population of the country…
  17. 17. Deep Dive into Data • To solve this problem, we created a new population collection • For each airport, the point is inserted if: – Within 100 KM – AND does not already exist in collection
  18. 18. Deep Dive into Data • We can now figure out the population on a State level • For each country x:
  19. 19. Deep Dive into Data
  20. 20. Deep Dive into Data
  21. 21. Apps and Visualizations
  22. 22. Summary • ICAO, UN SDGs & “No Country Left Behind” • Aviation Data-Driven Decision Making • Deep Dive into Data • Apps and Visualizations

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