Calamity Research Dataset
Multi-hazard event data with cascade risk models — built for disaster science.
What's in the dataset
Calamity aggregates, normalizes, and enriches disaster events from 250 scientific data sources worldwide. Every event is processed through an 11-step pipeline that assigns a CalamityScore (0-100), calculates population exposure using a gaussian decay model, and detects cascade interactions using 20 probabilistic rules derived from peer-reviewed literature.
Data Dictionary
| Field | Type | Description |
|---|---|---|
| id | string | Unique event identifier |
| type | enum | Disaster type (16 categories: earthquake, fire, flood, volcano, ...) |
| title | string | Human-readable event title |
| severity | enum | low | medium | high | critical |
| calamity_score | float | Composite risk score 0–100 (intensity 40%, population 30%, cascade 20%, historical 10%) |
| latitude / longitude | float | WGS84 coordinates |
| event_timestamp | ISO 8601 | Original source timestamp |
| reported_at | ISO 8601 | First detection by Calamity pipeline |
| source | string | Primary data source identifier |
| population_exposed | integer | PEI — Population Exposure Index (gaussian decay model) |
| population_radius_km | float | Exposure radius in km |
| country_code | ISO 3166 | Two-letter country code |
| nearest_city | string | Closest populated place |
| cascade_data | JSON | Array of cascade risk assessments with probability, type, radius, timeframe |
| type_metadata | JSON | Hazard-specific fields (magnitude, VEI, wind speed, AQI, ...) |
Export Formats
One row per event. Cascade data serialized as JSON column. Compatible with R, Python pandas, Excel.
Full event objects with nested cascade arrays. Ideal for programmatic analysis and web applications.
FeatureCollection with Point geometries. Direct import into QGIS, ArcGIS, Mapbox, Kepler.gl.
API Access
GET /archive/bulk-export?format=csv&from=2025-01-01&to=2026-01-01&type=earthquake # Filters: format, from, to, type, severity, min_score, include_cascades, limit # Max 500K events per export # API key required for authenticated tiers
Full API documentation available at /docs.
Risk Assessment Dataset — CFI Time Series
The Calamity Forecast Index (CFI) produces a risk assessment time series per country, hazard type, and day. Each record contains a 0-100 risk score, confidence level, and driver decomposition (cascade, return period, seasonal, trend, news velocity). The CFI estimates risk levels based on historical frequencies, seasonality, and current activity — it is not a prediction engine.
GET /api/v2/forecast → 95 countries × 16 hazard types × daily resolution → Fields: country_code, hazard_type, date, cfi (0-100), level (critical/high/elevated/moderate/low), drivers (text), components (cascade, return_period, seasonal, trend_anomaly, news_velocity) # Citable as time series for multi-hazard risk assessment # BibTeX available at /research#cite
How to Cite
If you use the Calamity dataset in your research, please cite it using the following BibTeX entry:
@dataset{calamity_dataset_2026,
author = {Leone Ventures},
title = {Calamity Multi-Hazard Event Dataset},
year = {2026},
publisher = {Leone Ventures},
url = {https://calamity.live/research},
note = {197-source aggregated disaster dataset with cascade risk models}
}Pricing
Available with .edu email
- ✓Full dataset access (10K events/download)
- ✓CSV + JSON export
- ✓5,000 API requests/day
- ✓14-day free trial
- ✓Full dataset access (500K events/download)
- ✓CSV + JSON + GeoJSON export
- ✓50,000 API requests/day
- ✓Cascade data included
- ✓DOI-citable dataset
- ✓14-day free trial
Methodology
Our cascade detection rules are based on peer-reviewed literature including Gill & Malamud (2014), the UNDRR Sendai Framework, and OASIS CAP v1.2 standards. The CalamityScore formula, population exposure model, and deduplication engine are fully documented in our methodology page.