A project focused on modernizing NASA's legacy datasets and making them accessible to the public through interactive visualizations. This application specifically analyzes planetary data to identify potentially habitable planets.
NASA's extensive data repository contains thousands of datasets spanning over six decades of scientific observations. However, many remain inaccessible due to obsolete data formatting practices from missions like Apollo and Voyager. Operation ZETA transforms complex raw data into easily digestible, interactive formats to promote broader usage in education, research, and public engagement.
- Frontend: React, Next.js, TypeScript
- Visualization: Python (Plotly, Pandas)
- Data Processing: Custom parsers for NASA legacy formats
- Database: MongoDB
- Styling: CSS Modules
- Node.js (v18 or higher)
- npm or yarn
- Python 3.x (for data processing scripts)
- MongoDB account (local or cloud)
- Clone the repository:
git clone https://github.com/fdac25/NASA.git
cd NASA- Install dependencies:
npm install
npm install particles.js- Set up MongoDB connection - Create a
.env.localfile in the root directory and add your MongoDB URI:
MONGODB_URI="mongodb+srv://<username>:<password>@planet-database.dhbvzdf.mongodb.net/?retryWrites=true&w=majority&appName=planet-database"Important: You must connect to the database by adding your MongoDB URI to
.env.localbefore running the application. Without this, the application will not be able to store or retrieve planetary data.
- Run the development server:
npm run dev- Open http://localhost:3000 in your browser
Our datasets are sourced from NASA's open data repositories, focusing on:
- Apollo mission data (solar wind measurements, lunar observations)
- Voyager mission data (Jupiter's atmosphere, outer planet surveys)
- Planetary statistics from various NASA missions
- Represents significant scientific milestones with high educational value
- Can be reasonably processed within project timeline
- Has formatting or accessibility challenges that demonstrate our modernization approach
University of Tennessee, Knoxville - EECS Department
- Zebulon Mcknight - Data Parsing & Dataset Selection Lead
- Eric Yang - Data Research & Frontend Design
- Trevor Eisenbacher - Python Visualizations & Documentation Lead
- Ahmed Ghazi - Web Application Development Lead
- October 1st: Dataset selection complete
- October 15th: Visualization tool development begins
- October 31st: Data cleansing complete
- November 15th: Visualization tool complete
- November 30th: Final product delivery
This is an academic project for UTK EECS. For questions or collaboration opportunities, please contact the team members listed above.
This project is developed as part of an academic program at the University of Tennessee, Knoxville.
- NASA for providing open access to decades of scientific data
- The Apollo and Voyager mission teams whose data we're working to preserve and modernize
- University of Tennessee EECS Department for project support
Data modernization, legacy format conversion, scientific data visualization, NASA datasets, habitable planets, educational resources, space exploration, public engagement
GitHub commands ! https://earthdatascience.org/workshops/intro-version-control-git/basic-git-commands/ CSS worskapce ! https://www.w3schools.com/css/css_image_transparency.asp