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README.md

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+---
+
+# 🎓 OpenAlex: The World's Scholarly Knowledge Graph
+
+> **174M scholarly works** from the world's largest open bibliographic database
+
+**OpenAlex Homepage:** https://openalex.org  
+**API Documentation:** https://docs.openalex.org  
+**Paper:** https://arxiv.org/abs/2205.01833
+
+## What is OpenAlex?
+
+🎓 **OpenAlex** is a free and open catalog of the global research system, containing metadata for **250M+ scholarly works**, **90M+ authors**, **120K+ venues**, and **100K+ institutions**. Named after the ancient Library of Alexandria, it serves as the successor to Microsoft Academic Graph.
+
+This Hugging Face dataset provides a streamlined subset of **174M scholarly works** with rich metadata, making it easy to:
+- 📊 Analyze research trends across disciplines
+- 🔗 Build citation networks and knowledge graphs  
+- 🤖 Train models for academic text understanding
+- 🔍 Develop scholarly search and recommendation systems
+
+## Dataset Overview
+
+### Quick Stats
+- **174M scholarly works** (papers, books, datasets, etc.)
+- **Multi-disciplinary coverage**: Medicine, Biology, Chemistry, Physics, Computer Science, Social Sciences, and more
+- **Rich metadata**: Titles, abstracts, authors, institutions, citations, concepts, and open access status
+- **Time span**: Publications from 1800s to present
+- **Languages**: Primarily English, with multilingual content
+
+### Key Features
+
+✅ **Comprehensive Metadata**
+- Unique identifiers (DOI, OpenAlex ID, arXiv, PubMed)
+- Publication details (title, date, venue, language)
+- Author and institutional affiliations
+- Citation counts and referenced works
+
+✅ **Open Access Information**
+- OA status and licensing
+- Repository locations
+- Full-text availability
+
+✅ **Concept Tagging**
+- Hierarchical subject classification
+- Auto-generated topic tags
+- Cross-disciplinary connections
+
+✅ **Quality Indicators**
+- Publication types
+- Peer review status
+- Citation metrics
+
+## Usage
+
+### Loading the Dataset
+
+```python
+from datasets import load_dataset
+
+# Load a sample (recommended for exploration)
+dataset = load_dataset("sumuks/openalex", split="train", streaming=True)
+
+# Iterate through examples
+for paper in dataset.take(100):
+    print(f"Title: {paper['title']}")
+    print(f"Year: {paper['publication_year']}")
+    print(f"Citations: {paper['cited_by_count']}")
+    print("---")
+```
+
+## License
+
+This dataset is released under the **Open Data Commons Attribution License (ODC-By) v1.0**, following OpenAlex's commitment to open science. You are free to share and adapt this data with proper attribution.
+
+## Citation
+
+If you use this dataset, please cite:
+
+```bibtex
+@article{priem2022openalex,
+  title={OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and concepts},
+  author={Priem, Jason and Piwowar, Heather and Orr, Richard},
+  journal={arXiv preprint arXiv:2205.01833},
+  year={2022}
+}
+```
+
+## Acknowledgments
+
+Special thanks to:
+- The [OurResearch](https://ourresearch.org/) team for creating and maintaining OpenAlex
+- [Arcadia Fund](https://www.arcadiafund.org.uk/) for funding OpenAlex development
+- The academic community for supporting open science initiatives
+
+---
+
+**Questions or Issues?** Open a discussion in the [Community tab](https://huggingface.co/datasets/sumuks/openalex/discussions) or visit [OpenAlex Help](https://help.openalex.org/)