docs/DATA_VALIDATION_REPORT.md

Data Validation Report: US Disasters Mashup

Validated: 2026-02-14 Dataset: disasters_mashup.json (13 MB, 54,575 records) Verdict: Authentic government data with known quality issues

Summary

54,575 records from four US government sources, all verified as authentic. Category-specific fields are well-populated where they apply. Two significant quality issues: aviation dates are truncated to year-only precision, and ~5,983 duplicate aviation records exist.

Dataset Composition

Category	Records	%	Source
Aviation Accidents	32,410	59.4%	NTSB
Severe Storms	14,770	27.1%	NOAA Storm Events
Earthquakes	3,742	6.9%	USGS
Shipwrecks	3,653	6.7%	NOAA AWOIS

Field Coverage

Fields are category-specific. Core fields (category, latitude, longitude, name, subcategory) are 100% populated across all records.

Field	Coverage	Present In
category	100%	All
latitude	100%	All
longitude	100%	All
name	100%	All (e.g., "Tornado in OKLAHOMA, KIOWA")
subcategory	100%	All (e.g., Tornado, Flash Flood, seismic, maritime, aviation)
date	94.3%	All except some historical shipwrecks
aircraft_type	59.4%	Aviation only (100% of aviation records)
event_id	59.4%	Aviation only (NTSB event IDs)
magnitude	19.9%	Storms (Fujita/EF scale) + Earthquakes (Richter)
fatalities	27.1%	Storms only
injuries	27.1%	Storms only
damage	26.4%	Storms only (text: "250K", "1.5M")
state	27.1%	Storms only
depth_km	0%	Field exists but all values null
vessel_type	0.6%	Shipwrecks, sparsely populated
cargo	<0.1%	Shipwrecks, almost empty

Coordinate Validation

• 100% populated, zero missing
• Latitude range: -77.4 to 82.2
• Longitude range: -179.3 to 178.8
• Coordinate precision: 5-6 decimal places (meter-level, consistent with GPS/survey data)
• Round coordinates: <1% (rules out synthetic generation)
• ~3,200 records outside CONUS bounds: expected for Hawaii, Alaska, territories, international aviation/maritime

Date Quality Issues

Storms: ISO 8601 dates with day precision (e.g., 1950-04-28). Range: 1950-2025. Clean.

Shipwrecks: Mixed formats (MM-DD-YYYY or null). 85.8% missing dates. Historical records dating to the 1600s. Expected for archival maritime data.

Aviation: All 32,410 dates truncated to YYYY-01-01. The real dates appear embedded in the event IDs (e.g., event_id 20121010X84549 suggests Oct 10, 2012, but date field shows 2012-01-01). This is a processing artifact, not fake data.

Earthquakes: Unix timestamps (e.g., 1766311037). Consistent with USGS API output format. Not converted to ISO 8601.

Duplicate Records

• 4,763 duplicate event IDs among aviation records
• 5,983 total extra records (some IDs appear 3+ times)
• Duplicates are exact copies (same coordinates, dates, all fields)
• Likely caused by overlapping source files during the original collection
• 18% duplication rate among records with event IDs

Synthetic Data Check

No synthetic data indicators found:

• Record counts are non-round (32,410 / 14,770 / 3,742 / 3,653)
• Geographic distribution matches known patterns (tornado alley, Pacific seismic belt, coastal aviation corridors)
• Storm subcategories show realistic distribution (Tornado: 6,334; Flash Flood: 2,358; Thunderstorm Wind: 2,257)
• Earthquake magnitudes range 4.5-8.2 with realistic distribution
• NTSB event IDs follow the official NTSB Event ID format (YYYYMMDD + sequence)
• Storm damage values use NOAA's text format conventions ("250K", "1.5M")

Storm Subcategory Breakdown

Top 10 storm types (from subcategory field):

1. Tornado: 6,334
2. Flash Flood: 2,358
3. Thunderstorm Wind: 2,257
4. Flood: 1,777
5. Hail: 1,246
6. Lightning: 574
7. Heavy Rain: 99
8. Marine Strong Wind: 43
9. Debris Flow: 43
10. Marine Thunderstorm Wind: 25

Known Issues

Issue	Severity	Notes
Aviation dates year-only	High	Real dates recoverable from event IDs
5,983 duplicate records	Medium	Deduplication on event_id would fix
Earthquake dates as timestamps	Medium	Valid data, just not human-readable
depth_km always null	Low	Field exists but never populated
cargo/vessel_type sparse	Low	Most shipwreck records lack this detail

Overall Assessment

Metric	Score
Source authenticity	10/10
Coordinate quality	9/10
Category-specific metadata	8/10
Date quality	6/10
Data cleanliness (duplicates)	7/10
Overall	8/10

Verdict: Authentic data from four government APIs. Well-structured with category-specific fields (storms have casualties and damage, aviation has aircraft types and NTSB IDs, earthquakes have magnitude). Two improvement opportunities: deduplicate aviation records and recover full dates from event IDs.