---
license: cc0-1.0
task_categories:
- text-classification
- object-detection
- information-retrieval
language:
- en
tags:
- uap
- ufo
- aviation
- government
- skywatch
- incident-reports
size_categories:
- 100<n<1K
---

# 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
```python
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
```python
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:
1. **PDF Processing**: 575 original PDF reports
2. **Text Extraction**: Native macOS OCR tools
3. **Structure Parsing**: Regex-based field extraction
4. **Image Generation**: PDF-to-PNG conversion
5. **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:

```bibtex
@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}
}
```

## License

This dataset contains government documents that are likely in the public domain. Users should verify the legal status for their specific use case.

## Contact

For questions about this dataset or to report issues, please open an issue in the repository.