Humanitarian Crisis Data Platform
End-to-end humanitarian crisis data platform — NLP-powered incident extraction, multi-source data integration, interactive dual-timeline visualization, and structured evidence archival across 6 data domains. No third-party data warehouse. Every pipeline built from scratch.
From raw news ingestion to structured JSON storage to interactive visualization — no third-party data warehouse or BI platform involved.
Flask + BeautifulSoup · Batch URL processing · Multi-source feeds
NLP · spaCy NER · Offline SQLite queue · Zero data loss
JSON / CSV schemas · Classification taxonomy · Source verification
Statistical aggregation · Trend detection · Severity scoring
Dual-timeline · Leaflet maps · Interactive charts · CSV export
Each domain features a custom schema supporting filtering, geographic mapping, temporal indexing, and CSV export — no external database engine.
Timestamped crisis events with location, type classification, casualty figures, and source attribution.
Structured casualty records with demographic breakdown, verification status, and family-level detail.
Attacks on protected sites — medical, educational, religious, water, and food infrastructure.
Nutrition, displacement, aid access, and economic indicators with trend analysis and threshold alerts.
Longitudinal event records spanning decades — normalized schema for cross-era comparative analysis.
Full evidence export per incident — structured JSON bundle with all linked records, sources, and metadata.
Analysts submit raw news article URLs; Flask parses content, runs spaCy NER entity recognition, and maps events to the incident taxonomy. Offline SQLite queue ensures zero data loss during connectivity gaps.
62 KB hand-built timeline manager renders historical records spanning decades and current incident streams simultaneously. Three view modes — Timeline, Map, and List — with CSV-powered data loading and advanced filtering.
Incidents plotted on interactive Leaflet maps with type-coded markers, zoom-level filtering, and click-through modals showing full incident detail with source attribution.
Dynamic JSON translation system with language detection and RTL-ready fallback. Supports 3+ locales for international humanitarian monitoring teams.
Full evidence export per incident — structured JSON bundle with all linked records, sources, and metadata. CSV export pipeline for all domains with one-click backup creation.
No personally identifiable data stored without consent. Source verification and attribution tracking on every record. OMOP CDM-compatible schema for analytics-database integration.
Every record carries a verified source chain — no anonymous data ingestion.
Built from scratch across 8 layers.
Whether you're an NGO, research institution, or journalist looking for structured humanitarian data tooling — let's talk.