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YAML Metadata Warning: The task_categories "information-retrieval" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

UAP/UFO Incident Reports Dataset

Dataset Summary

This dataset contains 575 Unidentified Aerial Phenomena (UAP) incident reports from the SKYWATCH system, spanning from 2007 to 2024. The reports include structured text data, metadata, and high-quality images extracted from official documents.

Dataset Structure

The dataset includes three modalities for each incident report:

1. Text Data (`text/`)

Raw text: Clean text extraction from original PDFs
Format: Plain text (.txt files)
Content: Complete incident reports with timestamps, locations, and detailed descriptions

2. Structured Metadata (`structured/`)

Format: JSON files with parsed fields
Fields:
- filename: Original document identifier
- extraction_timestamp: When the data was processed
- primary_code: Classification (UNIDENTIFIED AERIAL PHENOMENON, OTHER, etc.)
- date: Incident date and time
- status: Report status (Closed, Open, etc.)
- pod: Point of Defense location code
- reporting_facility: Facility that filed the report
- paged: Whether incident was paged
- remarks: Detailed incident description
- ufo_related_content: Extracted UFO/UAP-specific content

3. Images (`images/`)

Format: PNG images
Resolution: High-quality document scans
Content: Visual representation of original reports

Dataset Statistics

Total Reports: 575
Date Range: 2007-2024
Primary Classifications:
- Unidentified Aerial Phenomenon: 327 reports (56.9%)
- Other: 45 reports (7.8%)
- UAS (Unmanned Aerial Systems): 1 report
- Unknown/Null: 202 reports (35.1%)
Geographic Distribution:
- Denver (DEN): 365 reports (63.5%)
- National Capital Region (NCR): 9 reports (1.6%)
- Other/Unknown: 201 reports (35.0%)
Content Analysis:
- Reports mentioning "UFO": 266 (46.3%)
- Reports mentioning "radar": 71 (12.3%)

Notable Cases

The dataset includes several historically significant cases:

Balloon Boy Incident (237UAP00010): The famous 2009 hoax involving a helium balloon mistaken for a UFO
Multiple commercial aircraft encounters
Military and civilian pilot reports
Radar-tracked objects with no visible aircraft

Data Sources

All data was extracted from official SKYWATCH incident reports using automated processing:

OCR via native macOS pdftotext
Structured field extraction using regex patterns
Image conversion via macOS sips

Ethical Considerations

All data appears to be from official government sources
No personal identifying information is included
Reports focus on aerospace safety and unexplained phenomena
Data is being shared for research and transparency purposes

Usage Examples

Loading Text Data

from datasets import load_dataset

dataset = load_dataset("path/to/uap-incident-reports")

# Access text content
for example in dataset["train"]:
    print(f"Report {example['filename']}: {example['text'][:200]}...")

Analyzing Structured Data

import json

# Load structured metadata
with open("structured/237UAP00001.json") as f:
    report = json.load(f)
    
print(f"Date: {report['structured_fields']['date']}")
print(f"Location: {report['structured_fields']['pod']}")
print(f"Remarks: {report['structured_fields']['remarks']}")

Dataset Creation

The dataset was created through an automated pipeline:

PDF Processing: 575 original PDF reports
Text Extraction: Native macOS OCR tools
Structure Parsing: Regex-based field extraction
Image Generation: PDF-to-PNG conversion
Quality Assurance: 100% success rate validation

Limitations

OCR accuracy depends on original document quality
Some structured fields may be incomplete for older reports
Date formats vary across different time periods
Geographic coverage is primarily US-focused

Citation

If you use this dataset in your research, please cite:

@dataset{uap_incident_reports_2024,
  title={UAP/UFO Incident Reports Dataset: SKYWATCH System 2007-2024},
  author={Automated Extraction Pipeline},
  year={2024},
  publisher={Hugging Face},
  note={575 official incident reports with text, metadata, and images}
}