Knowledge Graph Visualization

Using OPAL, DBpedia & URIBurner

A Step-by-Step Guide to Interactive Data Visualization

Session Overview

What We'll Cover

  • Querying Linked Data - Access DBpedia using SPARQL endpoints
  • Agent-Based Processing - Leverage OPAL agents with LLMs
  • Data Transformation - Convert RDF knowledge graphs to visualizations
  • Interactive Design - Create engaging HTML infographics
  • Best Practices - Tips for production-ready implementations

System Architecture

Component Overview

DBpedia

Knowledge Graph

→

URIBurner

SPARQL Engine

→

OPAL Agent

AI Processing

→

HTML Output

Visualization

🎯 Key Benefit

This architecture separates data retrieval, processing, and presentation, enabling scalable and maintainable solutions for knowledge graph visualization.

Step 1: Understanding the Tools

Essential Components

🔧 URIBurner

  • SPARQL endpoint aggregator
  • RDF data transformation
  • Multiple query interfaces
  • Remote endpoint access

🤖 OPAL Agent

  • AI-powered data processing
  • Multiple LLM support
  • Function calling capabilities
  • Knowledge graph integration

📊 DBpedia

  • Structured Wikipedia data
  • Billions of RDF triples
  • Rich entity relationships
  • Public SPARQL endpoint

💎 Virtuoso

  • High-performance database
  • SPARQL query engine
  • Deployment platform
  • Scalable architecture

Step 2: Check Available Models

Verify LLM Access

URIBurner:getModels() // Check for specific provider URIBurner:getModels({ "provider": "gemini" }) // Returns available models including: // - gemini-2.5-pro // - gemini-2.5-flash // - claude-sonnet-4-20250514 // - gpt-4o

💡 Pro Tip

Always verify model availability before starting your workflow. Different models have different capabilities, costs, and rate limits.

Step 3: Configure OPAL Agent

Select Assistant & Model

  • Retrieve assistant configurations using assistantsConfigurations()
  • Select the Basic OPAL Agent (ID: system-my-new-basic-demo-agent)
  • Choose your LLM model (e.g., gemini-2.5-pro)
  • Set appropriate parameters: max_tokens, temperature, etc.
URIBurner:chatPromptComplete({ "assistant_config_id": "system-my-new-basic-demo-agent", "model": "gemini-2.5-pro", "max_tokens": 2000, "prompt": "Your query here..." })

Step 4: Craft Your Prompt

Instruct the Agent

📝 Effective Prompt Structure

Be specific about: (1) Data source, (2) Query requirements, (3) Output format, (4) Linking preferences

"Please query the DBpedia SPARQL endpoint to provide a list of movies directed by Spike Lee. Requirements: 1. Use a SPARQL query against http://dbpedia.org/sparql 2. Find all movies where Spike Lee is the director 3. Return movie titles with DBpedia IDs 4. Format results with proper hyperlinks Execute the query and format with proper hyperlinks."

Step 5: Process Agent Response

Understanding Output Structure

🔗 Entity URIs

Each result includes DBpedia resource URIs for direct linking to knowledge graph entities

📊 Structured Data

Results are organized with entity names, labels, and relationship information

🎯 Formatted Output

Agent provides pre-formatted markdown with hyperlinks ready for integration

✅ Validation

Built-in query validation ensures accurate and complete results

🎨 Next Step

Transform this structured data into an interactive visualization using HTML, CSS, and JavaScript

Step 6: Design Interactive Infographic

Key Design Principles

  • Entity-First Design: Center content around knowledge graph entities with proper hyperlinking to URIs
  • Modern Aesthetics: Use gradients, glassmorphism, smooth animations, and professional typography
  • Interactive Elements: Implement floating navigation, accordions, lightboxes, and scroll-triggered animations
  • Structured Metadata: Include comprehensive SEO with JSON-LD, Open Graph, and microdata formats
  • Performance Optimization: Use Intersection Observer API and efficient DOM manipulation

Essential Interactive Features

User Experience Elements

🎯 Navigation

  • Floating, draggable panel
  • Auto-hide after inactivity
  • Pin marker restoration
  • Smooth scrolling to sections

📱 Responsive Design

  • Mobile-optimized layouts
  • Touch-friendly interactions
  • Flexible grid systems

🎨 Visual Effects

  • Glassmorphism for panels
  • Card hover animations
  • Scroll-triggered fade-ins
  • Professional gradients

🔗 Entity Linking

  • Hyperlinked entities
  • Copyable section anchors
  • External URI integration

Technical Implementation

Code Structure

// Entity Linking Pattern const linkedDataBase = "https://linkeddata.uriburner.com/describe/?uri="; const entityURI = encodeURIComponent(dbpediaResource); const fullURL = linkedDataBase + entityURI; // Intersection Observer for Animations const observer = new IntersectionObserver((entries) => { entries.forEach(entry => { if (entry.isIntersecting) { entry.target.classList.add('visible'); } }); }, observerOptions); // State Management for Navigation let navState = { isVisible: true, isManuallyClosed: false, activityTimer: null };

SEO & Structured Data

Triple Metadata Strategy

1. JSON-LD

Schema.org structured data for search engines - provides rich context about entities and relationships

2. Open Graph (POSH)

Social media optimization tags for Facebook, LinkedIn - ensures proper preview cards when shared

3. Microdata

Inline semantic markup within HTML - enhances accessibility and machine readability

4. Twitter Cards

Twitter-specific metadata for enhanced sharing - optimizes appearance in Twitter feeds

🎯 Best Practice

Maintain consistency across all three metadata formats. Use identical descriptions and ensure all key entities are properly marked up.

Real-World Example

Spike Lee Filmography Visualization

📊 Input Data

  • 35+ films from DBpedia
  • Entity URIs for each movie
  • Director relationships
  • Metadata and labels

✨ Output Features

  • Interactive filmography grid
  • Career timeline visualization
  • Thematic analysis sections
  • FAQ with accordion UI

🎬 Result

A fully interactive, SEO-optimized HTML page with 35 hyperlinked films, smooth animations, floating navigation, and comprehensive metadata - all generated from a single SPARQL query.

Best Practices & Tips

Production-Ready Guidelines

  • Always Use Agents: Leverage OPAL agents rather than direct SPARQL calls for better error handling and formatting
  • Verify Model Availability: Check available LLMs before starting to ensure optimal performance and cost
  • Entity URI Pattern: Use the consistent pattern: https://linkeddata.uriburner.com/describe/?uri={encoded-uri}
  • State Management: Implement proper state tracking for interactive components (e.g., isManuallyClosed flags)
  • Performance: Use Intersection Observer API instead of scroll event listeners for better performance
  • Accessibility: Include proper ARIA labels, semantic HTML, and keyboard navigation support

Common Pitfalls to Avoid

Lessons Learned

❌ Direct SPARQL Calls

Avoid bypassing agents - they provide better error handling, formatting, and integration

❌ Forgetting URL Encoding

Always encode URIs when creating hyperlinks to avoid broken links with special characters

❌ Inconsistent Metadata

Ensure descriptions and titles match across JSON-LD, Open Graph, and microdata formats

❌ Poor State Management

Track user actions explicitly - don't let automated behaviors override manual user controls

❌ Scroll Event Overuse

Use Intersection Observer instead of scroll listeners for better performance and battery life

❌ Missing Mobile Support

Test responsive design thoroughly - touch interactions differ from desktop hover states

Advanced Features

Taking It Further

🎨 Visual Enhancements

  • Glassmorphism effects
  • Custom scroll bars
  • Parallax backgrounds
  • Animated SVG icons
  • 3D transformations

⚡ Functional Additions

  • Search functionality
  • Filter by category
  • Export to PDF
  • Share to social media
  • Print-optimized layouts

🚀 Next Level

Consider integrating real-time data updates, collaborative features, or embedding this as a component in larger applications using iframe or web components.

Use Cases & Applications

Where to Apply This Workflow

📚 Educational Content

Create interactive learning materials that link to authoritative knowledge sources

🔬 Research Visualization

Display academic relationships, citations, and research networks from knowledge graphs

📊 Business Intelligence

Visualize company data, market relationships, and competitive landscapes

🏛️ Cultural Heritage

Showcase museum collections, historical events, and cultural connections

🎬 Media & Entertainment

Present filmographies, discographies, and creative relationships

🏥 Healthcare & Sciences

Display medical ontologies, drug relationships, and scientific classifications

Tools & Resources

Essential Links

🔗 Platforms

  • OPAL: opal.openlinksw.com
  • URIBurner: linkeddata.uriburner.com
  • Virtuoso: virtuoso.openlinksw.com
  • DBpedia: dbpedia.org

📖 Documentation

  • SPARQL 1.1 Specification
  • RDF 1.1 Primer
  • Schema.org Vocabulary
  • OpenLink Documentation

💻 Code Libraries

Frontend: Tailwind CSS, Google Fonts, Intersection Observer API | Metadata: JSON-LD, Open Graph, Microdata | Animation: CSS Transitions, Transform, Backdrop-filter

Key Takeaways

Remember These Points

  • Agents Over Direct Queries: OPAL agents provide superior error handling, formatting, and LLM-powered enhancements
  • Triple Metadata Strategy: Implement JSON-LD, Open Graph, and microdata for maximum discoverability
  • Entity-Centric Design: Build visualizations around knowledge graph entities with proper URI linking
  • Performance First: Use modern APIs like Intersection Observer for efficient animations and interactions
  • User Intent Priority: Manual user actions should always override automated behaviors in your UI logic

Thank You!

Questions & Discussion

🔗 Learn More

OPAL: opal.openlinksw.com

URIBurner: linkeddata.uriburner.com

Documentation: virtuoso.openlinksw.com

Powered by OPAL | Deployed on Virtuoso

© 2025 OpenLink Software

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