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Free Global Conflict and Security Data Sources for GIS

A guide to free conflict and security datasets including ACLED political violence events, the Global Terrorism Database, and FEWS NET food security classifications for GIS analysis.

Conflict and security data is critical for humanitarian response, risk assessment, peace research, and policy analysis. Here are the best free global datasets for GIS.

ACLED — Armed Conflict Location & Event Data

ACLED provides the most comprehensive daily-updated dataset of political violence and protest events worldwide. Each event includes coordinates, date, event type (battles, explosions, protests, riots, strategic developments), involved actors, and fatality counts.

  • Coverage: Global (all countries)
  • Update frequency: Daily
  • Event types: 6 categories
  • Best for: Real-time conflict monitoring and humanitarian response

Global Terrorism Database (GTD)

The Global Terrorism Database from the University of Maryland provides data on over 200,000 terrorist incidents worldwide from 1970 to 2020, with 120+ variables per incident.

  • Coverage: Global
  • Temporal: 1970–2020
  • Attributes: Location, attack type, weapon, target, perpetrator group, casualties
  • Best for: Terrorism analysis and historical security research

FEWS NET Food Security

The Famine Early Warning Systems Network (FEWS NET) provides IPC food security phase classifications for 35+ food-insecure countries with current and projected scenarios.

  • Coverage: Africa, Asia, Latin America
  • Update frequency: Monthly
  • IPC phases: Minimal, Stressed, Crisis, Emergency, Famine
  • Best for: Food security monitoring and humanitarian planning

Using Conflict Data Responsibly

  1. Data quality varies by region — reporting bias may affect coverage.
  2. ACLED and GTD use different methodologies — ACLED is more frequent and real-time, GTD has more historical depth.
  3. Combine with population data from the Population & Census category for vulnerability analysis.
  4. All data can be analyzed locally using GeoDataViewer Studio.
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