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README.md

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+## 🌐 About OpenDataArena
 
-Edit this `README.md` markdown file to author your organization card.
+**OpenDataArena (ODA)** is an open research initiative devoted to evaluating, benchmarking, and creating high-value datasets for the post-training era of large language models (LLMs).  
+We believe **data quality defines model capability** — and that **open, reproducible evaluation** is key to accelerating progress in AI.
+
+ODA provides a **transparent and data-centric ecosystem** where diverse datasets — from instruction-following and code generation to reasoning and mathematics — can be fairly compared, analyzed, and continuously improved.
+
+---
+
+### 🚀 Our Mission  
+To make **data evaluation scientific, transparent, and community-driven**, while continuously **producing high-value, openly available datasets** that enhance model alignment and reasoning ability.
+
+---
+
+### 🔑 Key Features
+
+- 🏆 **Dataset Leaderboard** — [Leaderboard](https://opendataarena.github.io/leaderboard.html) ranks and visualizes the most valuable datasets across multiple domains, based on unified post-training benchmarks.  
+- 📊 **Comprehensive Scoring System** — [Scoring tool](https://github.com/OpenDataArena/OpenDataArena-Tool/tree/main/data_scorer) measures dataset quality, diversity, difficulty, and learning value using reproducible pipelines.  
+- 🧰 **Open-Source Toolkit** — *[OpenDataArena-Tool](https://github.com/OpenDataArena/OpenDataArena-Tool)* enables dataset curation, scoring, and analysis with a standardized, community-driven workflow.  
+- 🌱 **High-Value Data Generation** — beyond evaluation, ODA continuously produces and shares new, top-quality datasets for fine-tuning and alignment research.
+
+---
+
+If you find our work helpful, please consider ⭐ **starring** and **subscribing** to support open, data-driven AI research.  
+Learn more at [opendataarena.github.io](https://opendataarena.github.io).