Data Extraction System
Purpose:
This document describes Riskwolf's automated data extraction system that continuously collects environmental and geospatial data from authoritative global sources to support parametric insurance products.
1. System Overview
Riskwolf operates 12 specialized data extraction services that automatically collect, process, and deliver environmental risk intelligence. These services monitor real-time weather patterns, natural disasters, seismic activity, and administrative boundaries across global regions with focused capabilities in high-risk areas including Indonesia, Philippines, New Zealand, USA, etc.
System Capabilities
- Continuous Monitoring: 24/7 automated data collection from 12+ authoritative sources
- Global Coverage: Worldwide environmental monitoring with regional specialization
- Real-time Processing: Near real-time data availability for immediate risk assessment
- Historical Archives: Comprehensive historical datasets for trend analysis and model training
- Quality Assurance: Automated validation and processing with standardized formats
2. Active Data Extraction Services
2.1 Weather & Climate Services
ECMWF Data Services
- ERA5 Reanalysis: Historical weather analysis with total precipitation, temperature, snowfall, and wind components at 0.25° resolution globally
- IFS Forecasts: 15-day forecasts at ~9 km resolution; currently, we capture the first 7 days with 3-hour precipitation and temperature outputs.
Regional Weather Services
- CHIRPS: Daily global precipitation data from Climate Hazards Group at 0.05° resolution (50S-50N coverage)
- IMD Gridded Data: India Meteorological Department regional weather observations and forecasts for the Indian subcontinent
2.2 Natural Disaster Monitoring Services
Tropical Storm Tracking
- NOAA IBTrACS: International Best Track Archive providing cyclone locations, wind speeds, and pressure data globally
- Copernicus GDACS: Global Disaster Alert and Coordination System for real-time disaster alerts and storm information
Seismic Monitoring
- USGS Earthquake Services: Real-time and historical earthquake data including magnitude, PGA event maps, and epicenter locations
- Wildfire Monitoring: Previously sourced from the National Interagency Fire Center (USA). This service is currently inactive and requires re-establishment.
Severe Weather Services
- NOAA Storm Prediction Center: Real-time severe weather events and forecast products for USA tornado, hail, and storm tracking
2.3 Geographic Reference Services
Administrative Boundaries
- GADM: Global administrative boundaries (levels 0-5) from Database of Global Administrative Areas
- GeoBoundaries: Open-source administrative boundary data for geospatial referencing and territory definition
3. Data Extraction Process
3.1 Automated Data Collection
Service Architecture
Each data extraction service follows a standardized pattern:
- Containerized Python applications with consistent project structure
- Environment-based configuration for flexible deployment
- AWS S3 integration for secure data archival and access
- Docker containerization for reliable deployment across environments
Collection Methods
- API Integration: Direct connections to authoritative data providers with authentication management
- File Downloads: Automated retrieval from FTP servers and web sources
- Real-time Feeds: Continuous monitoring of live data streams from agencies like USGS and NOAA
- Scheduled Extraction: Time-based collection aligned with data provider update schedules
3.2 Data Processing Pipeline
Standardization Process
- Data Retrieval: Automated download from source with retry mechanisms for reliability
- Format Conversion: Transformation to standardized formats (GeoParquet, NetCDF4, GeoJSON)
- Quality Validation: Automated checks for completeness, accuracy, and format compliance
- Geographic Processing: Coordinate system standardization and spatial indexing
- Cloud Storage: Secure upload to AWS S3 with organized directory structure
Output Formats
- GeoParquet: Efficient spatial data format for earthquake and wildfire point data
- NetCDF4: Climate data standard for weather and precipitation datasets
- GeoJSON: Web-compatible format for administrative boundaries and geographic features
3.3 Monitoring and Reliability
Operational Monitoring
- Continuous health checks and service availability monitoring
- Automated retry mechanisms for network failures and source unavailability
- Data lineage tracking for audit requirements and quality assurance
- Real-time alerting for service disruptions or data quality issues
4. Data Availability and Access
4.1 Data Storage Architecture
Cloud Storage Organization
- Secure AWS S3 bucket storage with organized directory structure by provider, dataset, variable, and date
- Standardized file naming conventions for automated processing and retrieval
- Metadata files for data lineage tracking and quality assurance
- Optimized compression and chunking for efficient access and processing
4.2 Data Delivery Timeframes
Real-time Services (Minutes to Hours)
- USGS Earthquake Data: Available within minutes of seismic events
- NIFC Wildfire Data: Real-time wildfire location and status updates
- NOAA Severe Weather: Storm events and forecasts updated throughout the day
Near Real-time Services (1-7 Days)
- ERA5 Reanalysis: Historical weather data with ~7-day latency
- IMD Regional Data: India-specific weather with ~3-day latency
- NOAA IBTrACS: Tropical storm data within 2-5 days post-event
Scheduled Services (Weeks to Monthly)
- CHIRPS Precipitation: Final precipitation products available third week of following month
- Administrative Boundaries: Updated as source agencies release new boundary definitions
4.3 Data Quality Standards
Validation Framework
- Automated format validation and schema checking upon ingestion
- Geographic coordinate system verification and standardization
- Temporal consistency checks and gap identification
- Cross-reference validation with multiple data sources where available
5. Data Acquisition Monitoring
5.1 Operational Metrics
Timeliness Tracking
- Data latency measurement from source to availability
- SLA compliance monitoring
- Trend analysis for degradation detection
Completeness Monitoring
- Expected vs. actual data volume tracking
- Missing data gap identification
- Coverage area validation
5.2 Quality Indicators
Source Reliability
- Uptime tracking for data sources
- Error rate monitoring
- Historical reliability scoring
Data Freshness
- Age of data upon ingestion
- Update frequency compliance
- Staleness alerting
6. Integration with Quality Framework
The data gathering process integrates with Riskwolf's Data Quality Assurance framework through:
- Third-Party Outage Controls: Logging provider failures and service disruptions
- Required Inputs Validation: Ensuring all expected data sources are available
- File Integrity Checks: Validating successful downloads and transfers
7. Future Data Sources
Planned Integrations
- MERRA-2: NASA's atmospheric reanalysis with aerosol data
- BOM SILO: Australian Bureau of Meteorology climate data
- Regional Weather Services: Enhanced local meteorological data
Emerging Technologies
- IoT Sensor Networks: Direct sensor data integration
- Blockchain Oracles: Decentralized data verification
- Satellite Constellation APIs: Next-generation Earth observation data
7. Data Source References
For comprehensive technical specifications, implementation details, and parametric insurance applications of each data source, refer to the individual data source documentation:
Weather & Climate Sources
- ERA5-Land (ECMWF) - High-resolution land surface reanalysis
- IFS Forecasts (ECMWF) - Medium-range weather forecasts
- CHIRPS - Satellite-enhanced precipitation dataset
- IMD Gridded Rainfall - India-specific precipitation data
- IMD Gridded Temperature - India-specific temperature data
Natural Disaster Sources
- NOAA IBTrACS - Global tropical cyclone database
- Copernicus GDACS - Multi-hazard disaster alerts
- USGS Earthquake Hazards - Global seismic monitoring
For a complete overview of all available datasets with status and specifications, see the Data Sources Overview.