fa5680f0dd
- Introduced custodian_hub_v3.mmd, custodian_hub_v4_final.mmd, and custodian_hub_v5_FINAL.mmd for Mermaid representation. - Created custodian_hub_FINAL.puml and custodian_hub_v3.puml for PlantUML representation. - Defined entities such as CustodianReconstruction, Identifier, TimeSpan, Agent, CustodianName, CustodianObservation, ReconstructionActivity, Appellation, ConfidenceMeasure, Custodian, LanguageCode, and SourceDocument. - Established relationships and associations between entities, including temporal extents, observations, and reconstruction activities. - Incorporated enumerations for various types, statuses, and classifications relevant to custodians and their activities.
156 lines
5.2 KiB
Markdown
156 lines
5.2 KiB
Markdown
# Heritage Custodian Frontend Implementation Plan
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## Executive Summary
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This document outlines the implementation plan for a web-based frontend application to visualize and explore Heritage Custodian Linked Data from the RDF schemas located in `/schemas/20251121/rdf/`. The frontend will be built using modern web technologies, leveraging patterns from the example_ld project while extending them for the specific needs of heritage institution data visualization.
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## Project Objectives
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### Primary Goals
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1. **Interactive RDF Visualization**: Display Heritage Custodian data from multiple RDF formats
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2. **UML Diagram Rendering**: Convert Mermaid/PlantUML diagrams to interactive D3.js visualizations
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3. **SPARQL Query Interface**: Enable semantic queries against the RDF data
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4. **Multi-format Support**: Handle Turtle, JSON-LD, N-Triples, RDF/XML, and other RDF serializations
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5. **Responsive Design**: Mobile-first approach for accessibility across devices
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### Secondary Goals
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1. **Data Export**: Enable users to download filtered/queried data in various formats
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2. **Provenance Tracking**: Visualize data lineage and quality tiers
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3. **Geographic Mapping**: Interactive maps showing institution locations
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4. **Temporal Navigation**: Timeline views for organizational change events
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5. **Network Visualization**: Display relationships between institutions
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## Key Deliverables
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### 1. Frontend Application
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- React/TypeScript single-page application
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- Component library for RDF visualization
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- D3.js integration for complex visualizations
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- SPARQL query builder interface
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### 2. Backend Services
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- RDF triple store (Apache Jena Fuseki or Oxigraph)
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- GraphQL API for efficient data fetching
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- WebSocket support for real-time updates
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- Caching layer for performance
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### 3. Documentation
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- User guide for navigation and features
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- Developer documentation for extension
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- API documentation for backend services
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- Deployment guide for production setup
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## Technology Stack
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### Frontend
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- **Framework**: React 18 with TypeScript
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- **State Management**: Zustand or Redux Toolkit
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- **Styling**: Tailwind CSS + Shadcn/ui components
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- **Visualization**: D3.js v7, Cytoscape.js, Leaflet
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- **RDF Processing**: N3.js, rdflib.js
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- **Build Tool**: Vite
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### Backend
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- **Runtime**: Node.js 20 LTS or Deno
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- **Framework**: Fastify or Hono
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- **RDF Store**: Apache Jena Fuseki or Oxigraph
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- **Cache**: Redis
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- **Database**: PostgreSQL with PostGIS for geographic data
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### Infrastructure
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- **Container**: Docker with multi-stage builds
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- **Orchestration**: Docker Compose for development
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- **CI/CD**: GitHub Actions
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- **Monitoring**: Prometheus + Grafana
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## Implementation Phases
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### Phase 1: Foundation (Weeks 1-2)
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- Project setup and configuration
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- Basic RDF loading and parsing
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- Initial component library
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- Simple list and detail views
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### Phase 2: Core Visualization (Weeks 3-4)
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- D3.js integration for UML diagrams
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- Network graph visualization
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- Geographic mapping
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- Timeline components
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### Phase 3: Query Interface (Weeks 5-6)
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- SPARQL query builder
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- Faceted search
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- Advanced filtering
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- Results visualization
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### Phase 4: Enhancement (Weeks 7-8)
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- Performance optimization
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- Export functionality
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- User preferences
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- Documentation
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### Phase 5: Production (Week 9)
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- Deployment setup
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- Monitoring integration
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- Security hardening
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- Launch preparation
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## Success Metrics
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### 1. Performance
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- Initial load time < 3 seconds
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- RDF parsing < 500ms for 10,000 triples
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- Smooth 60fps interactions
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### 2. Usability
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- Mobile responsive design
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- WCAG 2.1 AA compliance
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- Intuitive navigation
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### 3. Functionality
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- Support for all RDF formats in `/schemas/20251121/rdf/`
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- Complete SPARQL 1.1 query support
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- Export in 5+ formats
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## Risk Mitigation
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| Risk | Impact | Mitigation |
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|------|---------|------------|
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| Large RDF files causing performance issues | High | Implement pagination, virtualization, and progressive loading |
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| Complex SPARQL queries timing out | Medium | Query optimization, caching, timeout limits |
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| Cross-browser compatibility | Medium | Progressive enhancement, polyfills, thorough testing |
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| D3.js learning curve | Low | Leverage existing examples, consider alternative libraries |
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## Team Structure
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- **Frontend Developer**: React components, D3.js visualizations
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- **Backend Developer**: RDF store, API development
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- **UX Designer**: Interface design, user flows
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- **DevOps Engineer**: Infrastructure, CI/CD
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- **QA Engineer**: Testing, accessibility
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## Timeline
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- **Week 1-2**: Foundation phase
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- **Week 3-4**: Core visualization
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- **Week 5-6**: Query interface
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- **Week 7-8**: Enhancement
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- **Week 9**: Production deployment
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- **Week 10+**: Maintenance and iteration
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## Next Steps
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1. Review and approve implementation plan
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2. Set up development environment
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3. Create initial project structure
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4. Begin Phase 1 implementation
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## Related Documents
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- [01-architecture.md](01-architecture.md) - System architecture design
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- [02-design-patterns.md](02-design-patterns.md) - Frontend design patterns
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- [03-tdd-strategy.md](03-tdd-strategy.md) - Test-driven development approach
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- [04-example-ld-mapping.md](04-example-ld-mapping.md) - Reusable modules from example_ld
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- [05-d3-visualization.md](05-d3-visualization.md) - D3.js UML visualization strategy
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