DataTerminology.comNEW
Also known as: KG
Graph-structured knowledge base linking entities and relationships with semantics for integration, querying, and reasoning.
DESCRIPTION
A knowledge graph organizes data as nodes (entities) and edges (relationships), often with schema and semantics. It supports flexible integration across sources, entity resolution, and rich querying via SPARQL or graph traversals. Implementations use RDF triple stores or property graph databases. Knowledge graphs power search, recommendations, and analytics by capturing context and meaning. They enable inference with ontologies and rules for deeper insights.
ALTERNATIVE DEFINITIONS
Wikipedia
A knowledge graph is a knowledge base that uses a graph-structured data model or topology to integrate data.
Positions knowledge graphs as integration-focused, graph-structured knowledge bases.
Google Developers
The Knowledge Graph is a knowledge base used by Google to enhance its search engine’s results with information gathered from a variety of sources.
Describes a prominent industrial-scale implementation and purpose.
RELATED TERMS
Knowledge Representation RDF OWL SPARQL Linked Data Graph Database Triple Store Property Graph Entity Resolution Schema.org
COMPETING TERMS
Relational Database Document Database
RELATIONS
- Broader: Graph
KNOWLEDGE AREAS
Semantic & Knowledge Modeling AI Data Architecture Data Integration & Interoperability
TARGET AUDIENCE
Data Architect Data Engineer AI Engineer Data Scientist Data Modeler
EXTERNAL SOURCES
- Wikipedia - Knowledge graph
- W3C - RDF primer for graph-based data
- Neo4j - Vendor guide to knowledge graphs
- Schema.org - Vocabulary for entities and relationships
TOP QUESTIONS
Why use a Knowledge Graph instead of a relational database?
Knowledge graphs model relationships first, enabling flexible schema evolution and complex connections without costly joins.
Category: Relevancy
What standards underpin Knowledge Graphs?
RDF, RDFS/OWL for semantics, and SPARQL for querying are widely used standards.
Category: Definition
How do Knowledge Graphs support reasoning?
Ontologies and rules enable inference, deriving new facts from existing triples and class hierarchies.
Category: Concept
What are common mistakes when building a Knowledge Graph?
Skipping clear ontology design, mixing identifiers, and ignoring data provenance lead to brittle graphs.
Category: Mistakes
Where are Knowledge Graphs used in practice?
Search, recommendations, master data linking, regulatory compliance, and data catalogs are common applications.
Category: Example
How is entity resolution handled in Knowledge Graphs?
Use matching rules, embeddings, and authority identifiers (e.g., ORCID, ISBN) to merge duplicates.
Category: How-to
What is the difference between RDF and property graphs?
RDF uses triples with global semantics; property graphs attach key-value properties to nodes and edges, often with vendor-specific query languages.
Category: Misunderstanding
How do you govern a Knowledge Graph?
Define ontology stewardship, naming conventions, provenance, versioning, and quality checks on ingestion.
Category: Best practices
Can Knowledge Graphs integrate unstructured data?
Yes, via entity extraction and linking from text, images, or tables into graph entities and relations.
Category: Requirements