A comprehensive patent analytics ecosystem with 12 specialized modules, 200+ Jupyter notebooks, and production-ready tools for patent information professionals, PATLIB staff, and patent office personnel. This repository demonstrates modern approaches to patent data analysis using EPO data sources, advanced visualization techniques, and scalable architectures.
This toolkit has evolved into a complete patent intelligence platform featuring modular Python packages, interactive web applications, extensive training materials, and specialized analysis workflows. With 400+ Python files and comprehensive documentation, it addresses everything from basic classification browsing to advanced market intelligence analysis.
Production-ready patent intelligence platform with comprehensive modular architecture:
- Full-featured CLI and Python package with 185+ source files
- Analyzers: technology, regional, applicant, and trend analysis modules
- Data access: PATSTAT, EPO OPS, IPC/CPC, and geographic data providers
- Visualizations: charts, maps, dashboards with factory pattern
- Complete test suite and development tools
- YAML-driven configuration for flexibility
Patent intelligence framework with data provider abstractions:
- Unified data provider interface for multiple patent databases
- Modular analyzer and processor architecture
- Configuration-driven analysis workflows
- Real connection testing and validation
PATLIB demonstration tools with extensive archive of development iterations:
- REE (Rare Earth Elements) patent analysis demonstrations
- 100+ archived trial runs with complete session documentation
- Enhanced notebooks for market intelligence correlation
- Business intelligence and geographic analysis pipelines
German university patent analysis using EPO Deep Tech Finder data:
- Complete CLI application with modular ETL pipeline
- University-specific analysis and reporting tools
- EPO OPS API integration with authentication handling
- Legacy notebooks with analysis results and visualizations
Rare Earth Elements patent landscape analysis with comprehensive market intelligence:
- Structured development phases from templates to live demonstrations
- Citation network analysis and geographic intelligence
- Market data correlation and business intelligence reporting
- Multiple trial runs with complete documentation
Patent family visualization tools (Credit: Anonymous EPO Examiner):
- Interactive patent family tree generation and relationship analysis
- Python modules for patent family processing
- Visual examples of complex patent family structures
Modern SvelteKit-based web application for exploring patent classification hierarchies (Credit: Matze):
- SvelteKit framework with multiple visualization modes
- Radial tree visualization for hierarchical IPC/CPC exploration
- Sankey flow diagrams and circle packing views
- Real-time switching between IPC and CPC classification systems
- Performance-optimized for large datasets (15,000+ nodes)
- Professional-grade visualization for patent researchers
SQLite-based classification browser with interactive tree visualization (Credit: Tatjana, Johnny, Marc):
- Python-based classification database and Plotly visualizations
- SQLite storage for IPC classification data (2025 scheme)
- Interactive database building and tree exploration notebooks
EPO OPS API integration for IPC data querying:
- Authentication utilities and API access tools
- Interactive tutorial notebooks for OPS workflows
- Python modules for automated IPC analysis
PATSTAT-based IPC analysis with comprehensive statistical workflows:
- IPC subclass analysis and trend visualization
- Classification distribution and technology mapping
- Integration with PATSTAT Global database
Experimental IPC tools for classification exploration:
- Interactive classification browsing utilities
- Exploratory analysis notebooks
Geographic patent distribution analysis (Presented at EPO Patent Knowledge Forum 2024):
- NUTS region integration with district-level patent analysis
- Interactive maps using PyGWalker
- Federal state comparison and regional trend tools
- Custom visualization configurations for German patent data
Comprehensive training ecosystem with 80+ educational notebooks (Credit: EPO and WIPO):
- PATSTAT in-depth: Complete table-by-table documentation (30+ TLS tables, 25+ REG tables)
- EP Fulltext: European patent full-text analysis tutorials
- EPAB: EPO Patent Analytics Bootcamp materials
- OEPM: Spanish Patent Office gender analysis examples
- WIPO Handbook: Complete patent analytics handbook with R examples
Extensive input data and reference materials:
- REE Material: Rare earth elements research data, market reports, classification lists
- GEO Mappings: NUTS region boundaries and geographic reference data
- EPO PATSTAT Handbooks: Official documentation and user manuals
- CLAUDE Coding: Claude Code documentation and training materials
- 12 Specialized Modules - From experimental tools to production platforms
- 200+ Jupyter Notebooks - Training, analysis, and demonstration workflows
- 400+ Python Files - Comprehensive source code across all modules
- 4 Main Python Packages - Production-ready tools with CLI interfaces
- 2 Web Applications - Modern interactive visualization tools
- 80+ Training Notebooks - Complete educational ecosystem
- Patent Information Professionals: Production-ready analytics platforms and advanced tools
- PATLIB Staff: Demonstration materials, training resources, and practical examples
- Patent Office Personnel: Workflow automation, analysis templates, and integration tools
- Researchers & Academics: Methodological approaches and comprehensive case studies
- Data Scientists: Technical implementation patterns and scalable architectures
- Production Platforms: Full-featured patent intelligence systems with modular architecture
- Multi-Database Integration: EPO OPS, PATSTAT, DeepTechFinder, USGS, and geographic databases
- Advanced Visualizations: Interactive web apps, classification explorers, geographic maps, and citation networks
- Market Intelligence: Patent-market correlation analysis with business intelligence reporting
- Educational Ecosystem: Complete training materials from basic tutorials to advanced workflows
- Geographic Analysis: NUTS-compliant regional statistics and district-level patent mapping
- Classification Tools: Interactive IPC/CPC hierarchy exploration and analysis utilities
Each module contains its own README.md and CLAUDE.md with specific setup instructions. See INVENTORY_REPORT.md for comprehensive component overview.
# PizNet - Full patent intelligence platform
cd piznet/
pip install -e .
python patent_intelligence.py --help
# PatIntelli - Data provider framework
cd patintelli/
pip install -r requirements.txt
python patent_intelligence.py# Modern classification explorer
cd ipc-tree-explorer/
npm install && npm run dev
# Classification database browser
cd ipc-browser/
# See setup instructions in module README- Python 3.8+ with Jupyter Lab/Notebook
- Node.js 18+ for web applications
- EPO Developer Account for OPS API access
- PATSTAT Database Access for advanced analytics
This toolkit represents ongoing work in patent analytics education and tool development. Contributions, suggestions, and use case examples are welcome from the patent information community.
- IPC Browser: Developed by Tatjana Stojadinovic, Johnny Debray, and Marc Haus (2019-2020)
- IPC Tree Explorer: Developed by Matze
- Family Tree Tools: Contributed by Anonymous EPO Patent Examiner
- Training Materials: Provided by EPO (European Patent Office) and WIPO (World Intellectual Property Organization)
- Regional Mappings: Presented at EPO Patent Knowledge Forum 2024
Please refer to individual directories for specific licensing information. Training materials may have separate license terms from the EPO.