1 / 15

Analyzing 40+ Years of Terrorism Data: Insights from The Shadow of Terror Project

"The Shadow of Terror" project by Bijoy Raveendran at the National Institute of Design compiles a comprehensive dataset of over 200,000 records detailing every terrorist incident from 1970 to 2011. This dataset encompasses critical information about each attack, including the date, location, group name, casualties, weapons used, and motives. By employing data visualization tools like TileMill and MapBox, the project aims to create impactful visual representations of terrorism trends, emphasizing the significance of numbers and threat levels while fostering a deeper understanding of global terrorism.

malise
Télécharger la présentation

Analyzing 40+ Years of Terrorism Data: Insights from The Shadow of Terror Project

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related