https://github.com/thytranx/datalens

Datalens aims to enable interactive 3D exploration of complex, multi-dimensional datasets. Designed for intuitive usability, it is accessible to users without advanced programming skills or specialized hardware.
https://github.com/thytranx/datalens

3d-visualization data-visualization glfw3 opengl

Last synced: 2 months ago
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Datalens aims to enable interactive 3D exploration of complex, multi-dimensional datasets. Designed for intuitive usability, it is accessible to users without advanced programming skills or specialized hardware.

• Host: GitHub
• URL: https://github.com/thytranx/datalens
• Owner: thytranx
• License: mit
• Created: 2025-02-09T23:11:42.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-04-26T02:58:38.000Z (about 1 year ago)
• Last Synced: 2025-04-26T03:41:39.623Z (about 1 year ago)
• Topics: 3d-visualization, data-visualization, glfw3, opengl
• Language: C++
• Homepage:
• Size: 23.4 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# DataLens

**A Next-Generation 3D Data Visualization Platform**  

*Bridging the Gap Between Complex Data and Actionable Insights*

---

## Table of Contents  

- [Project Overview](#project-overview)  

- [Key Features](#key-features)  

- [Use Cases](#use-cases)  

- [System Architecture](#system-architecture)  

- [Installation](#installation)  

- [Usage Examples](#usage-examples)  

- [Methodology](#methodology)  

- [Milestones & Goals](#milestones--goals)  

- [Testing & Quality](#testing--quality)  

- [Contributing](#contributing)  

- [License](#license)  

---

## Project Overview  

**DataLens** addresses critical limitations in modern data visualization tools by:  

- 🚀 Providing **GPU-accelerated 3D rendering** via OpenGL  

- 🔍 Enabling **intuitive exploration** of billion-point datasets  

- 🤖 Integrating **AI-assisted analysis** through conversational interfaces  

- 🌐 Supporting cross-domain applications from genomics to financial modeling  

Target Users:  

- Researchers ∙ Engineers ∙ Data Analysts ∙ Journalists ∙ Educators  

---

## Key Features  

### Core Modules  

| **Data Management**               | **Visualization Engine**          |   **Interaction System**            |  **AI Assistant**               |

|-----------------------------------|-----------------------------------|-------------------------------------|---------------------------------|

| - PDB/CFD/CSV/JSON/3D Point Clouds  | - OpenGL 3 rendering              | - 6DOF camera controls              | - NLP-powered query parsing     |

| - Octree/k-d Tree optimizations   | - Dynamic LOD scene management    | - Real-time data slicing/filtering  | - Context-aware recommendations |

| - PCA-based dimensionality reduction | - Customizable visual mappings | - Collaborative annotation tools    | - Automated insight generation  |

### Performance Targets  

✅ **30+ FPS** with 10M+ data points  

✅ **<2s** load time for 1GB datasets  

✅ **Multi-threaded** data preprocessing  

---

## Use Cases  

| Domain            | Application                      | Key Functionality                  |  

|-------------------|----------------------------------|-------------------------------------|  

| **Genomics**       | 3D protein structure analysis    | - VR-ready molecular visualization |  

| **CFD**            | Fluid dynamics visualization     | - 4D spacetime slicing tools       |  

| **Finance**        | Market trend exploration         | - Interactive 3D bubble charts     |  

| **Data Journalism**| Immersive storytelling            | - AR annotation overlays           |  

**[See full use case details](#use-cases)**  

---