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THE SHADOW OF TERROR

THE SHADOW OF TERROR. BIJOY RAVEENDRAN INFORMATION & INTERFACE DESIGN. JULY 26 2013 | NATIONAL INSTITUTE OF DESIGN. 30 years of every terrorist incident from 1970 – 2011 (200K records) Retrieved from the Global Terrorism DB

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THE SHADOW OF TERROR

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  1. THE SHADOW OF TERROR BIJOY RAVEENDRAN INFORMATION & INTERFACE DESIGN JULY 26 2013 | NATIONAL INSTITUTE OF DESIGN

  2. 30 years of every terrorist incident from 1970 – 2011 (200K records) • Retrieved from the Global Terrorism DB • Date of attack, place of attack, group name, target, casualities, weapons used, damages, motive, descriprion • Supplementary information from Wikipedia DATASET DATASET

  3. ‘Exploratory’ more than ‘explanatory’ • Data is in the form of events – so have a timeline and plot it on a map • No story at the moment – so emphasize on the numbers and threat level • Gather supplementary information from Wikipedia CONSIDERATIONS CONSIDERATIONS

  4. ITERATION INITIAL ITERATIONS

  5. Markers on map can be represented as explosions (or the color of fire) • Use opacity to show overlapping layers or use ‘no-overlap’ (ruled out later) • Make the map borderless , add more negative space around content, so emphasis goes to subject matter • Tree maps a better option over bar charts for • summary data CONSIDERATIONS CONSIDERATIONS (contd.)

  6. Scaled down dataset (30 years to 7 years) • Removed unused data columns • Removed ‘invalids’ • 0 or unknown month/day/year • Unknown city/state/country • 0 casualities/wounded and 0/unknown damages SANITIZING DATA SANITIZING DATA

  7. Used Google’s ‘Geo’ API to geo-tag locations • Pivot tables based on ‘terrorist organizations’, ‘country of attack’, and ‘mode of attack’ columns. • Formula to calculate severity of attack based on following data: • Number of people killed • Number of people wounded • Estimated damage to property ENRICHING DATA ENRICHING DATA

  8. Severity • = ( dead_index * 10 + • wounded_index * 7.5 + • damage_index * 2.5 ) • Wound_Index • 0-75 : 1 • 75-150 : 2 • 150-225 : 3 • 225-300 : 4 • >300: 5 • Dead_Index • 0-40 : 1 • 40-80 : 2 • 80-120 : 3 • 120-160 : 4 • 160 – 200 : 5 • Damage_Index • <1million : 1 • 1m – 1b : 2 • >1b : 3 ENRICHING DATA ENRICHING DATA (contd.)

  9. Excel for data/business logic • TileMill for map creation • MapBox for map hosting • Google Docs for geo-coding • Google Visualization API to generate tree-maps • HTML/Javascript for layout • For proposed future use : • MapBox.js/Wax for custom tooltips/legend • Flash for intro screen TOOLS TOOLS

  10. SEE VISUALIZATION NOW! Goto visualization

  11. ‘Invalids’ may be incidents of high severity • TileMill rejects non geo-coded locations – skews the numbers • Geo-coding API is not entirely accurate – combination of city/country not yielding better results. May have to manually encode. ERRORS SOURCES OF ERROR

  12. All deaths are considered the same – shouldn’t assassinations be considered to be of higher priority? • Large data shown as “############” • If ‘others’ occurs in any of the top 10 visualizations, it has been ignored ERRORS SOURCES OF ERROR

  13. Incorporate complete data set • Complete other sections • Include opening sequence to set up the story • Adding animation to map markers will help emphasize more on numbers FUTURE PLANS FUTURE PLANS

  14. Link tooltip to related news article (probably for high severity incidents) • Remove top 5 countries from tree-map. Have a choroplethic view on country wise impact instead. • Include – ‘Your country has XX% chance of being attacked’ • Use different color marker to represent zero casuality attacks • Match-ups FUTURE PLANS FUTURE PLANS

  15. THANK YOU JULY 26 2013 | NATIONAL INSTITUTE OF DESIGN

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