Science Video Database

📚 Prior Work & Research Contributions

Overview

The Science Video Database represents prior work that demonstrates the creation of a curated, searchable database of scientific video content. This project establishes a foundation for integrating video-based learning and research content into the CopernicusAI Knowledge Engine, enabling multi-modal knowledge exploration through searchable transcripts and filtered scientific video content.

🔬 Research Contributions

• Curated Video Collection: Filtered scientific videos from YouTube and other sources
• Transcript-Based Search: Searchable video database using transcript content
• Multi-Disciplinary Coverage: Biology, chemistry, CS, mathematics, physics
• Integration Framework: Designed for CopernicusAI Knowledge Engine integration

⚙️ Technical Achievements

• Hybrid Search System: Transcript-based search with filtering capabilities
• Ingestion Pipeline: Automated video ingestion and transcript processing
• Vector Database Integration: Support for semantic search using embeddings
• Scalable Architecture: Designed for scaling from 2k to 200k+ videos

🎯 Position Within CopernicusAI Knowledge Engine

The Science Video Database serves as a multi-modal content component of the CopernicusAI Knowledge Engine, providing:

• Video content integration for learning
• Transcript search for research discovery
• Multi-modal learning support

• Research Paper linking potential
• AI Podcast enhancement

This work establishes a proof-of-concept for AI-assisted video content management in scientific research, demonstrating how searchable transcripts can enable systematic discovery and integration of video-based knowledge.

🎬 Live Demo

Access the live Science Video Database application with searchable transcripts and curated video content.

🔬 Open Science Video Database

🚀 Project Milestones

Prototype (Current)

• 10-15 channels, ~2k videos
• Basic ingestion pipeline
• Transcript storage
• Hybrid search UI with filters

Alpha (Next Phase)

• 50+ channels, 20k videos
• Personalization MVP
• Email digests
• Improved UX polish

Scaling (Future)

• 200k videos
• Autoscaling workers
• Admin dashboard
• Automated QA

🔧 Technical Architecture

Frontend

• Next.js 14
• React Server Components
• Hybrid search UI

Backend

• Node.js/TypeScript
• Serverless functions
• Ingestion worker

Database

• PostgreSQL
• Vector DB
• Search Engine

Cloud

• Google Cloud Platform
• Vertex AI
• Cloud Run

🔗 Related Projects

🔬 CopernicusAI

Main knowledge engine that can integrate video content with AI podcasts and research synthesis.

Visit CopernicusAI →

📚 Research Paper Metadata Database

Potential integration for linking videos to research papers and metadata.

Visit Metadata Database →

🧬 GLMP

Biological process visualization that could link to related educational videos.

Explore GLMP →

🛠️ Programming Framework

Process analysis tool that could utilize video content for process explanations.

Explore Framework →

How to Cite This Work

Welz, G. (2024–2025). Science Video Database.
Hugging Face Spaces. https://huggingface.co/spaces/garywelz/sciencevideodb

This project serves as infrastructure for AI-assisted video content discovery in scientific research, enabling systematic search and integration of video-based knowledge through transcript-based discovery.

The Science Video Database is designed as infrastructure for AI-assisted science, providing multi-modal content discovery capabilities within the CopernicusAI Knowledge Engine.