Knowledge Graphs - Semantic Data Modeling | Tags

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Geode’s native graph model provides an ideal foundation for building enterprise knowledge graphs that capture complex domain knowledge and relationships. <h3 id="what-is-a-knowledge-graph" class="position-relative d-flex align-items-center group"> What is a Knowledge Graph? <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="what-is-a-knowledge-graph" aria-haspopup="dialog" aria-label="Share link: What is a Knowledge Graph?"> Share link </button> </h3>A knowledge graph is a structured representation of real-world entities (people, places, concepts, events) and their relationships. Unlike traditional relational databases that store data in tables, knowledge graphs emphasize connections between data points, making it easier to discover hidden relationships and derive new insights. Key characteristics: <ul> <li>Entities: Real-world objects represented as nodes with properties</li> <li>Relationships: Typed connections between entities with optional properties</li> <li>Semantic meaning: Labels and relationship types convey domain semantics</li> <li>Schema flexibility: Easily evolve the graph structure as understanding grows</li> </ul> <h3 id="building-knowledge-graphs-with-geode" class="position-relative d-flex align-items-center group"> Building Knowledge Graphs with Geode <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="building-knowledge-graphs-with-geode" aria-haspopup="dialog" aria-label="Share link: Building Knowledge Graphs with Geode"> Share link </button> </h3>Creating entities: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Create entities with semantic labels CREATE (company:Organization:Company { name: 'Acme Corporation', founded: 1985, industry: 'Technology' }); CREATE (person:Person:Employee { name: 'Alice Smith', title: 'Chief Technology Officer', expertise: ['distributed systems', 'graph databases'] }); CREATE (concept:Concept:Technology { name: 'Graph Database', category: 'Data Management', description: 'Database using graph structures for semantic queries' }); </code></pre></div>Establishing relationships: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Connect entities with semantic relationships MATCH (alice:Person {name: 'Alice Smith'}), (acme:Company {name: 'Acme Corporation'}) CREATE (alice)-[:WORKS_FOR {since: 2018, role: 'CTO'}]->(acme); MATCH (alice:Person {name: 'Alice Smith'}), (graphdb:Technology {name: 'Graph Database'}) CREATE (alice)-[:HAS_EXPERTISE_IN {level: 'expert'}]->(graphdb); </code></pre></div> <h3 id="knowledge-graph-query-patterns" class="position-relative d-flex align-items-center group"> Knowledge Graph Query Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="knowledge-graph-query-patterns" aria-haspopup="dialog" aria-label="Share link: Knowledge Graph Query Patterns"> Share link </button> </h3>Traversing relationships: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Find all technologies a person has expertise in MATCH (person:Person {name: 'Alice Smith'})-[:HAS_EXPERTISE_IN]->(tech:Technology) RETURN tech.name, tech.category; -- Find colleagues with shared expertise MATCH (alice:Person {name: 'Alice Smith'})-[:HAS_EXPERTISE_IN]->(tech:Technology), (colleague:Person)-[:HAS_EXPERTISE_IN]->(tech) WHERE colleague <> alice RETURN DISTINCT colleague.name, collect(tech.name) AS shared_expertise; </code></pre></div>Path finding for knowledge discovery: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Discover connection paths between entities MATCH path = shortestPath( (company:Company {name: 'Acme'})-[*..6]-(target:Company {name: 'Competitor'}) ) RETURN path; </code></pre></div> <h3 id="use-cases" class="position-relative d-flex align-items-center group"> Use Cases <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="use-cases" aria-haspopup="dialog" aria-label="Share link: Use Cases"> Share link </button> </h3>Enterprise knowledge management: Capture organizational knowledge, expertise, and relationships for better decision-making and knowledge discovery. Semantic search: Enable intelligent search that understands context and relationships, not just keywords. Recommendation systems: Leverage entity relationships for personalized recommendations based on user preferences and behavior patterns. Data integration: Unify data from disparate sources into a coherent knowledge graph that reveals cross-domain insights. <h3 id="related-topics" class="position-relative d-flex align-items-center group"> Related Topics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="related-topics" aria-haspopup="dialog" aria-label="Share link: Related Topics"> Share link </button> </h3><ul> <li><a href="/tags/graph-model/" >Graph Modeling</a> </li> <li><a href="/tags/property-graph/" >Property Graphs</a> </li> <li><a href="/tags/pattern-matching/" >Pattern Matching</a> </li> <li><a href="/tags/graph-analytics/" >Graph Analytics</a> </li> <li><a href="/tags/data-model/" >Data Modeling</a> </li> </ul>

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Knowledge Graphs - Semantic Data Modeling

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