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| Research Paper Metadata Database · Gary Welz · CUNY Graduate Center | |
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| <h1 class="text-4xl sm:text-5xl font-bold mb-4">62,000+ research papers, browsable and searchable</h1> | |
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| Research paper metadata serving GLMP, ATAP, and CopernicusAI. | |
| Updated daily. | |
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| <a href="https://storage.googleapis.com/regal-scholar-453620-r7-podcast-storage/papers-database-table.html" | |
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| 🚀 View Working Prototype → | |
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| <!-- Prior Work & Research Contributions --> | |
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| <h2 class="text-3xl font-bold text-gray-900 mb-6">📚 Role & Contributions</h2> | |
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| <h3 class="text-xl font-semibold text-gray-900 mb-4">Overview</h3> | |
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| The Research Paper Metadata Database is the structured metadata repository for scientific research | |
| papers across the CopernicusAI suite, updated daily. It provides the foundation for using AI tools | |
| to visualize and analyze the structure of scientific research, enabling systematic exploration of | |
| research patterns, citation networks, and interdisciplinary connections. | |
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| <h3 class="text-lg font-semibold text-gray-900 mb-3">🔬 Research Contributions</h3> | |
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| <li>• <strong>Structured Metadata Repository:</strong> Centralized database of research paper metadata</li> | |
| <li>• <strong>AI-Powered Preprocessing:</strong> LLM-based entity extraction and annotation</li> | |
| <li>• <strong>Citation Network Analysis:</strong> Cross-reference linking and relationship mapping</li> | |
| <li>• <strong>Integration Framework:</strong> Designed for CopernicusAI Knowledge Engine integration</li> | |
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| <h3 class="text-lg font-semibold text-gray-900 mb-3">⚙️ Technical Achievements</h3> | |
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| <li>• <strong>JSON-Based Storage:</strong> Structured metadata format for programmatic access</li> | |
| <li>• <strong>Entity Extraction:</strong> Automated extraction of genes, proteins, compounds, equations</li> | |
| <li>• <strong>Quality Assessment:</strong> Automated quality scoring and relevance metrics</li> | |
| <li>• <strong>API Architecture:</strong> RESTful API design for external access</li> | |
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| <h3 class="text-lg font-semibold text-gray-900 mb-3">🎯 Position Within CopernicusAI Knowledge Engine</h3> | |
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| The Research Paper Metadata Database serves as a <strong>core data infrastructure component</strong> of the CopernicusAI Knowledge Engine, providing: | |
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| <li>• Foundation for knowledge graph construction</li> | |
| <li>• Integration with AI podcast generation</li> | |
| <li>• Support for GLMP source references</li> | |
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| <li>• Science Video Database integration</li> | |
| <li>• Programming Framework support</li> | |
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| This is the data layer for AI-assisted research metadata management — structured data that | |
| enables systematic analysis and visualization of scientific research patterns. | |
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| <!-- Project Goals --> | |
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| <h2 class="text-3xl font-bold text-gray-900 mb-6">🎯 Project Goals</h2> | |
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| This project creates a database of scientific research paper metadata for the purpose of: | |
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| <ul class="text-gray-700 space-y-2"> | |
| <li>• Using AI tools to visualize and analyze the structure of scientific research</li> | |
| <li>• Expanding research in interesting, useful, and practical ways</li> | |
| <li>• Enabling systematic exploration of research patterns and connections</li> | |
| <li>• Supporting knowledge graph construction and semantic search</li> | |
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| <h2 class="text-3xl font-bold text-gray-900 mb-6">🔧 Technical Architecture</h2> | |
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| <h3 class="text-lg font-semibold text-gray-800 mb-3">Metadata Structure</h3> | |
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| <li>• DOI, arXiv ID, publication info</li> | |
| <li>• Abstracts & key findings</li> | |
| <li>• Extracted entities</li> | |
| <li>• Citation networks</li> | |
| <li>• Paradigm shift indicators</li> | |
| <li>• Quality scores</li> | |
| </ul> | |
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| <h3 class="text-lg font-semibold text-gray-800 mb-3">AI-Powered Preprocessing</h3> | |
| <ul class="text-sm text-gray-600 space-y-1"> | |
| <li>• LLM-based entity extraction</li> | |
| <li>• Automatic categorization</li> | |
| <li>• Keyword extraction</li> | |
| <li>• Citation tracking</li> | |
| <li>• Quality assessment</li> | |
| </ul> | |
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| <h3 class="text-lg font-semibold text-gray-800 mb-3">Integration Features</h3> | |
| <ul class="text-sm text-gray-600 space-y-1"> | |
| <li>• DOI/arXiv ID resolution</li> | |
| <li>• Cross-reference linking</li> | |
| <li>• Podcast-to-paper tracking</li> | |
| <li>• Search & query capabilities</li> | |
| <li>• API access</li> | |
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| <h2 class="text-3xl font-bold text-gray-900 mb-6 text-center">🔗 Related Projects</h2> | |
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| <h3 class="text-xl font-semibold text-gray-900 mb-3">🔬 CopernicusAI</h3> | |
| <p class="text-gray-600 mb-4"> | |
| Main knowledge engine integrating metadata with AI podcasts and research synthesis. | |
| </p> | |
| <a href="https://huggingface.co/spaces/garywelz/copernicusai" | |
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| Visit CopernicusAI → | |
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| <h3 class="text-xl font-semibold text-gray-900 mb-3">🧬 GLMP</h3> | |
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| Genome Logic Modeling Project using metadata for source paper references. | |
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| Explore GLMP → | |
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| <h3 class="text-xl font-semibold text-gray-900 mb-3">🛠️ Programming Framework</h3> | |
| <p class="text-gray-600 mb-4"> | |
| Universal process analysis tool that can utilize metadata for research analysis. | |
| </p> | |
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| Explore Framework → | |
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| <h3 class="text-xl font-semibold text-gray-900 mb-3">🎬 Science Video Database</h3> | |
| <p class="text-gray-600 mb-4"> | |
| Video content management with potential metadata linking. | |
| </p> | |
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| Visit Video Database → | |
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| <!-- How to Cite This Work --> | |
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| <h2 class="text-3xl font-bold text-gray-900 mb-6">How to Cite This Work</h2> | |
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| <p class="text-gray-800 font-mono text-lg leading-relaxed mb-4"> | |
| Welz, G. (2024–2025). <em>Research Paper Metadata Database</em>.<br> | |
| Hugging Face Spaces. https://huggingface.co/spaces/garywelz/metadata_database | |
| </p> | |
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| <p class="text-gray-700 mb-2"> | |
| This project serves as infrastructure for AI-assisted research analysis, enabling systematic visualization and exploration of scientific research patterns through structured metadata management. | |
| </p> | |
| <p class="text-gray-700 font-semibold"> | |
| The Research Paper Metadata Database is designed as infrastructure for AI-assisted science, providing the foundational data layer for knowledge graph construction and semantic search capabilities within the CopernicusAI Knowledge Engine. | |
| </p> | |
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| <p class="text-lg font-semibold mb-2">Research Paper Metadata Database</p> | |
| <p class="text-sm opacity-75">Part of the CopernicusAI Knowledge Engine</p> | |
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