infinite-agents-public/SDG_NETWORK_ANALYSIS.md

16 KiB

SDG Network Visualization - Analysis & Strategy

Executive Summary

I've analyzed the existing SDG network modelling project and designed a web-enhanced infinite loop system that will progressively generate sophisticated force-directed network visualizations with automatic API discovery.

What Was Reviewed

Existing SDG Network Project (ai_docs/sdg-network-modelling/):

  • Python notebooks fetching UN SDG API data
  • D3.js v3 force-directed graph visualization
  • Basic network showing: Geographic areas ↔ Ecosystem Capitals ↔ SDGs ↔ Targets
  • Simple interactions: hover tooltips, drag nodes
  • Single API source (UN Statistics)

Current Limitations:

  • Outdated D3.js version (v3 vs current v7)
  • Single hardcoded API
  • Basic visual design (simple circles/lines)
  • Limited interactivity (just hover)
  • No progressive enhancement
  • No web learning integration

New System Design

Architecture Overview

┌─────────────────────────────────────────────────────────────────┐
│  Web-Enhanced Infinite Loop (/project:infinite-web)            │
│                                                                 │
│  ┌──────────────┐      ┌──────────────┐      ┌──────────────┐ │
│  │   Phase 0:   │  →   │   Phase 1:   │  →   │   Phase 2:   │ │
│  │ Web Priming  │      │ Spec + Web   │      │    API       │ │
│  │              │      │   Analysis   │      │  Discovery   │ │
│  └──────────────┘      └──────────────┘      └──────────────┘ │
│         ↓                      ↓                      ↓        │
│  Fetch D3.js docs      Read spec file         Search for APIs  │
│  Learn force graphs    + priming knowledge    Parse Swagger    │
│                                                                 │
│  ┌──────────────┐      ┌──────────────┐      ┌──────────────┐ │
│  │   Phase 3:   │  →   │   Phase 4:   │  →   │   Phase 5:   │ │
│  │  Iteration   │      │   Parallel   │      │   Quality    │ │
│  │  Strategy    │      │   Agents     │      │  Assurance   │ │
│  └──────────────┘      └──────────────┘      └──────────────┘ │
│         ↓                      ↓                      ↓        │
│  Map URLs to iters     Launch sub-agents       Verify outputs  │
│  Plan API sources      Each learns + builds    Check API usage │
└─────────────────────────────────────────────────────────────────┘

Progressive Enhancement Strategy

Phase 1: Foundation (Iterations 1-5)

  • Modern D3.js v7
  • Single API per iteration
  • Node sizing, color coding, labels
  • Basic interactivity (drag, zoom, click)
  • Learn from: D3.js fundamentals, force simulation basics

Phase 2: Intermediate (Iterations 6-12)

  • Combine 2-3 APIs
  • Multi-property encoding (color + border)
  • Edge bundling, curved edges
  • Search, filter, side panels
  • Learn from: Advanced D3 techniques, data integration

Phase 3: Advanced (Iterations 13-20)

  • 4+ API sources
  • Clustering algorithms, community detection
  • Real-time data updates
  • Graph metrics dashboards
  • Learn from: Graph algorithms, streaming data

Phase 4: Expert (Iterations 21+)

  • Federated API queries
  • ML-based layouts
  • AI-powered insights
  • 3D/VR capabilities
  • Learn from: Cutting-edge research, novel techniques

API Discovery System

Automatic Discovery Process

Each iteration performs web searches to find new APIs:

// Search patterns (from sdg_network_url_strategy.json)
"environmental data API swagger site:github.com"
"scientific data REST API openapi"
"sustainable development goals API JSON"
"atmospheric weather data API free"
"water quality watershed API REST"
"forest biodiversity data API open source"
"NOAA ocean marine data API"
"NASA earth observation API"

Target API Domains

Environmental:

  • OpenAQ (air quality)
  • EPA APIs (environmental protection)
  • USGS Water Services
  • Global Forest Watch

Scientific:

  • GBIF (biodiversity)
  • NASA Earthdata
  • NOAA (ocean, weather, climate)
  • Seismic/earthquake data (USGS)

Sustainable Development:

  • UN SDG API (baseline)
  • World Bank Open Data
  • OECD Statistics
  • WHO Global Health
  • FAO Agricultural Data

Data Integration:

  • Swagger/OpenAPI spec parsing
  • Automatic entity mapping to nodes/edges
  • Cross-API entity resolution
  • Data quality assessment

Network Data Model

Node Structure

{
    id: "unique_id",
    name: "Display Name",
    type: "entity_type",        // country, indicator, species, etc.
    group: "category",           // for color coding
    size: value,                 // visual size from data
    properties: {
        value: number,
        unit: "string",
        timestamp: "date",
        source_api: "api_name",
        // ... domain-specific attributes
    }
}

Edge Structure

{
    source: "node_id",
    target: "node_id",
    type: "relationship",        // correlation, dependency, etc.
    strength: value,             // for force simulation
    weight: value,               // visual width
    properties: {
        correlation: number,
        confidence: number,
        source_api: "api_name"
    }
}

Visual Enhancement Progression

Node Enhancements

Foundation:

  • Size ← data magnitude
  • Color ← category
  • Labels with smart positioning

Intermediate:

  • Border color ← secondary property
  • Icon overlays ← entity type
  • Clustering ← community detection

Advanced:

  • Shape ← entity class
  • Opacity ← confidence level
  • Animation ← state changes

Expert:

  • 3D projection ← multi-dimensional data
  • ML-based positioning
  • Anomaly highlighting

Edge Enhancements

Foundation:

  • Width ← relationship strength
  • Color ← relationship type
  • Arrows ← directionality

Intermediate:

  • Curved paths ← visibility
  • Bundling ← clarity
  • Dash patterns ← relationship class

Advanced:

  • Animated flow ← data transfer
  • Dynamic strength ← real-time values
  • Hierarchical bundling ← complex relationships

Expert:

  • Probabilistic rendering
  • Predicted relationships
  • Causal inference visualization

Web Learning Integration

URL Strategy Structure

The system uses specs/sdg_network_url_strategy.json with:

Foundation URLs (Iterations 1-5):

  • D3.js fundamentals
  • Basic force-directed graphs
  • Color scales and node styling
  • Interactive tooltips

Intermediate URLs (Iterations 6-12):

  • Force-based clustering
  • Custom force implementations
  • Advanced color schemes
  • Animated transitions

Advanced URLs (Iterations 13-20):

  • Edge bundling algorithms
  • 3D projections
  • Adaptive rendering
  • Real-time data integration

Expert URLs (Iterations 21+):

  • Graph theory algorithms
  • ML-enhanced layouts
  • Multi-view interfaces
  • Export capabilities

Learning Process Per Iteration

  1. WebFetch assigned URL
  2. Extract 1-3 specific techniques
  3. Implement in visualization
  4. Document source and learnings
  5. Demonstrate improvement

File Structure

Created Files

specs/
├── sdg_network_progressive.md          # Main specification
└── sdg_network_url_strategy.json       # Learning URLs

SDG_NETWORK_GUIDE.md                    # Complete usage guide
SDG_NETWORK_ANALYSIS.md                 # This file (analysis)
CLAUDE.md                                # Updated with SDG commands

Output Structure

sdg_viz/                                 # Created by command
├── sdg_viz_1.html                       # Iteration 1
├── sdg_viz_2.html                       # Iteration 2
├── ...
└── sdg_viz_N.html                       # Iteration N

Each HTML file is self-contained with:

  • D3.js v7 force-directed graph
  • API data fetching
  • Interactive controls
  • Documentation footer (APIs used, web learning)

Usage Examples

Quick Start

claude
> /project:infinite-web specs/sdg_network_progressive.md sdg_viz 1

Output: sdg_viz/sdg_viz_1.html

  • UN SDG API baseline
  • Basic D3.js force graph
  • Foundation-level enhancements

Small Batch

> /project:infinite-web specs/sdg_network_progressive.md sdg_viz 5

Output: 5 files, each with:

  • Different API source
  • Progressive D3 techniques
  • Building on previous iterations

Full Progressive Learning

> /project:infinite-web specs/sdg_network_progressive.md sdg_viz 12 specs/sdg_network_url_strategy.json

Output: 12 iterations

  • Iterations 1-5: Foundation (basic graphs, single APIs)
  • Iterations 6-12: Intermediate (multi-API, advanced interactivity)

Infinite Mode

> /project:infinite-web specs/sdg_network_progressive.md sdg_viz infinite specs/sdg_network_url_strategy.json

Runs until context limit:

  • Progressive difficulty waves
  • Automatic API discovery
  • Increasingly sophisticated visualizations

Key Innovations

1. Automatic API Discovery

  • Old: Hardcoded UN SDG API only
  • New: Web searches find Swagger/OpenAPI endpoints
  • Impact: Unlimited data source expansion

2. Progressive Web Learning

  • Old: Static implementation
  • New: Each iteration learns from curated web resources
  • Impact: Continuous technique improvement

3. Multi-Source Integration

  • Old: Single API
  • New: Combine 2-5+ APIs per iteration
  • Impact: Richer, more insightful networks

4. Modern D3.js

  • Old: D3.js v3 (2012)
  • New: D3.js v7 (2023)
  • Impact: Better performance, modern features

5. Rich Interactivity

  • Old: Basic hover tooltip
  • New: Search, filter, zoom, click actions, exports, real-time updates
  • Impact: Deeper data exploration

Quality Metrics

Each iteration evaluated on:

Data Richness

  • API sources count (1 → 5+)
  • Node count
  • Edge count
  • Update frequency

Visual Quality

  • Color sophistication
  • Label readability
  • Animation smoothness (60fps target)
  • Layout clarity score

Interactivity

  • Feature count
  • Response time
  • Filter capabilities
  • Information density

Technical Innovation

  • New techniques applied
  • Performance metrics
  • Code quality
  • Browser compatibility

Comparison: Old vs New

Aspect Old System New System
D3 Version v3 (2012) v7 (2023)
APIs 1 (hardcoded) Unlimited (auto-discovery)
Node Styling Basic circles Size, color, border, icons, shapes
Edge Styling Simple lines Width, color, curves, bundling, animation
Interactivity Hover only Hover, click, drag, zoom, search, filter
Learning None Web-sourced techniques per iteration
Data Sources UN SDG only Environmental, scientific, SDG, health, etc.
Architecture Static Progressive enhancement
Output Single file Iteration series

Next Steps

Immediate Actions

  1. Test Single Iteration:

    claude
    > /project:infinite-web specs/sdg_network_progressive.md sdg_viz 1
    
  2. Review Output:

    • Open sdg_viz/sdg_viz_1.html in browser
    • Check UN SDG API integration
    • Test basic interactivity
    • Verify web learning attribution
  3. Generate Small Batch:

    > /project:infinite-web specs/sdg_network_progressive.md sdg_viz 5
    
  4. Compare Iterations:

    • See API diversity
    • Note progressive improvements
    • Identify new techniques applied

Advanced Exploration

  1. Custom API Focus:

    • Modify spec to target specific domains (ocean, climate, etc.)
    • Adjust search templates for specific APIs
  2. Algorithm Comparison:

    • Generate iterations with different force algorithms
    • Compare layout effectiveness
  3. Real-time Dashboards:

    • Generate iterations 13-20 for real-time features
    • Test streaming data integration
  4. Infinite Mode:

    > /project:infinite-web specs/sdg_network_progressive.md sdg_viz infinite specs/sdg_network_url_strategy.json
    

Customization Options

Create Domain-Specific Specs:

# Ocean/marine networks
cp specs/sdg_network_progressive.md specs/ocean_network.md
# Edit to focus on ocean APIs

# Climate change networks
cp specs/sdg_network_progressive.md specs/climate_network.md
# Edit to focus on climate APIs

Extend URL Strategy:

  • Add new D3 technique URLs
  • Add domain-specific learning resources
  • Create custom search templates

Modify Output Format:

  • Change from single HTML to multi-file
  • Add server-side API proxies
  • Generate dashboards with multiple views

Success Indicators

Technical Success

  • Modern D3.js v7 implementation
  • Multiple API sources per iteration
  • Self-contained HTML files
  • 60fps animations
  • No console errors

Functional Success

  • Force-directed graphs render correctly
  • API data fetches successfully
  • Interactivity works smoothly
  • Visualizations are informative
  • Error handling is graceful

Learning Success

  • Each iteration demonstrates new technique
  • Web sources are properly attributed
  • Progressive improvement is evident
  • API diversity increases
  • Complexity grows appropriately

User Value

  • Insights are actionable
  • Exploration is intuitive
  • Data relationships are clear
  • SDG analysis is enhanced
  • Visualizations are shareable

Troubleshooting Guide

API Access Issues

Problem: API requires authentication Solution: Iterations handle gracefully with fallback APIs

Problem: CORS errors Solution: Use CORS proxies or alternative APIs

Problem: Rate limiting Solution: Implement caching and request throttling

Performance Issues

Problem: Large graphs lag Solution: Canvas rendering (implemented in advanced iterations)

Problem: Slow force simulation Solution: Adaptive sampling, LOD techniques

Browser Compatibility

Problem: Old browser issues Solution: Target modern browsers, provide fallbacks

Resources

Documentation

  • SDG_NETWORK_GUIDE.md - Complete usage guide
  • specs/sdg_network_progressive.md - Specification
  • specs/sdg_network_url_strategy.json - Learning URLs
  • CLAUDE.md - Project overview

Reference

  • ai_docs/sdg-network-modelling/ - Original baseline
  • Observable HQ - D3.js examples
  • GitHub public-apis - API directory

Commands

  • .claude/commands/infinite-web.md - Implementation
  • /project:infinite-web - Run command

Conclusion

The new SDG Network Visualization system transforms a static, single-API visualization into a progressive, web-learning-enhanced, multi-API discovery system that:

  1. Discovers new data sources automatically via web search
  2. Learns advanced techniques from curated web resources
  3. Integrates multiple APIs into rich network visualizations
  4. Enhances progressively across iterations
  5. Documents sources and learnings clearly

This system leverages the web-enhanced infinite loop pattern to create increasingly sophisticated SDG network visualizations that provide genuine value for sustainable development insights and data exploration.

The system is ready to run. Start with:

claude
> /project:infinite-web specs/sdg_network_progressive.md sdg_viz 1