UAP Analysis Software: A Comprehensive Tool for Exploratory Data Analysis of Unidentified Anomalous Phenomena

Our tool aims to standardize UAP data analysis methodologies and facilitate collaborative research in the scientific community. By providing a user-friendly interface for complex data processing and analysis tasks, it enables researchers to focus on interpreting results and drawing insights from UAP data.

Explore Analysis Tool Here

Key Features

1. Feature Parsing with Large Language Models (LLMs)
   • Parse relevant information from unstructured reports into structured data.
   • Customizable JSON templates for tailored parsing.
   • Enables structured data analysis with classic statistical methods.

features_parsing.mp4

2. Semantic Search and Summarization

• Implements semantic search across multiple columns using natural language queries.
• Ranks and sorts dataset based on query relevance.
• Summarize and query multiple reports

3. Interactive Data Filtering and Visualization
   • User-friendly interface for applying multiple filters to the dataset.
   • Dynamic visualization of filtered data using various plot types (treemaps, histograms, line plots, bar charts).
   • Supports both categorical and numerical data analysis.
   • Creates interactive visualizations for cluster analysis and feature correlations.

4. Magnetic Data Analysis

   • Retrieves magnetic field data from INTERMAGNET geomagnetic stations.
   • Correlates magnetic data with UAP sighting times and locations.
   • Implements FastDTW (Dynamic Time Warping) for aligning potential anomalous geomagnetic signatures across multiple sightings.
   • Visualizes individual and aggregated magnetic data for analysis.

   

5. Geospatial Visualization

   • Interactive map interface for visualizing UAP sightings.
   • Incorporates layers for military bases, nuclear power plants, and UAP sightings.
   • Allows filtering and updating of map data based on various attributes.

6. Data Processing and Analysis Pipeline
   • Utilizes UMAP and HDBSCAN for clustering UAP reports and visualizing clusters.
   • Employs XGBoost for feature importance analysis in UAP classifications.
   • Performs statistical analyses including V-Cramer correlation and chi-square tests.
   • Implements parallel processing for improved performance on large datasets.

Contributing

Please feel free to contribute to this project by submitting a pull request or opening an issue.

License

This project is licensed under the MIT License - see the LICENSE file for details.