Understand Semantic Technology
Plain-English explanations of knowledge graphs, ontologies, RDF, SPARQL, OWL, Graph RAG, and more — written by practitioners, not theorists.
Knowledge Graph
A knowledge graph is a structured representation of real-world entities - people, products, concepts, events - and the relationships between them. Unlike tables in a relational database, a knowledge graph stores data as a network of interconnected nodes and edges, making it possible to traverse complex relationships, uncover hidden patterns, and answer questions that span multiple data sources.
what is a knowledge graphDigital Twin
A digital twin is a virtual replica of a physical asset, process, or system that is continuously updated with real-world data. By combining sensor feeds, engineering models, and contextual knowledge in a structured graph, a digital twin enables organisations to simulate scenarios, predict failures, and optimise performance without touching the physical counterpart.
what is a digital twinOntology
In information science, an ontology is a formal, explicit specification of a shared conceptualisation. It defines the types of things (classes), their properties, and the relationships between them within a particular domain. Ontologies give knowledge graphs their structure and enable machines to reason about data in meaningful ways.
what is an ontologyGraph RAG
Graph RAG (Graph-based Retrieval-Augmented Generation) is a technique that enhances large language models (LLMs) by grounding their responses in structured knowledge graph data. Instead of relying solely on vector similarity search over documents, Graph RAG traverses a knowledge graph to retrieve precise, contextualised facts - reducing hallucinations and enabling answers that cite their sources.
what is graph RAGSemantic Search
Semantic search is an approach to information retrieval that understands the meaning and intent behind a query, rather than simply matching keywords. By leveraging ontologies, knowledge graphs, and natural language processing, semantic search delivers results based on conceptual relevance - returning what the user meant, not just what they typed.
what is semantic searchData Fabric
A data fabric is an architecture that uses metadata, knowledge graphs, and semantic technologies to provide a unified, intelligent layer of data access across an organisation. Rather than physically moving all data into one place, a data fabric connects data where it lives - across clouds, databases, APIs, and file systems - and makes it discoverable, governed, and queryable through a shared semantic model.
what is a data fabricRDF
RDF (Resource Description Framework) is a W3C standard for representing information as a set of statements called triples. Each triple consists of a subject, predicate, and object - for example, “London — isCapitalOf — United Kingdom”. By giving every entity and relationship a unique URI, RDF makes data globally unambiguous, linkable, and machine-readable.
what is RDFLinked Data
Linked data is a set of principles for publishing structured data on the web so that it can be interlinked and become more useful. Coined by Tim Berners-Lee, the four linked data principles are: use URIs to name things, use HTTP URIs so people can look them up, provide useful information when someone looks up a URI (using RDF and SPARQL), and include links to other URIs so that more things can be discovered.
what is linked dataSPARQL
SPARQL (SPARQL Protocol and RDF Query Language) is the W3C standard query language for retrieving and manipulating data stored in RDF format. Like SQL for relational databases, SPARQL is the primary interface for querying knowledge graphs and triplestores - but unlike SQL, it is designed for graph traversal, pattern matching across relationships, and federated queries across multiple data sources.
what is SPARQLOWL (Web Ontology Language)
OWL (Web Ontology Language) is a W3C standard for defining ontologies - formal descriptions of the types of things, properties, and relationships in a domain. OWL goes beyond simple taxonomies by supporting logical axioms, class expressions, and property restrictions that enable automated reasoning: machines can infer new facts from existing data based on the rules encoded in the ontology.
what is OWL ontologySHACL
SHACL (Shapes Constraint Language) is a W3C standard for validating RDF graphs against a set of conditions called shapes. Where an ontology defines what types of things can exist, SHACL defines what valid data actually looks like - specifying required properties, value ranges, cardinality constraints, and structural patterns that data must conform to.
what is SHACLTriplestore
A triplestore is a specialised database designed to store and retrieve data in the form of RDF triples - subject-predicate-object statements. Unlike relational databases that use tables, or document stores that use JSON, a triplestore is optimised for graph-shaped data, enabling efficient traversal of relationships and native support for SPARQL queries.
what is a triplestoreAI Fabric
An AI fabric is an enterprise architecture that integrates knowledge graphs, data pipelines, machine learning models, and AI services into a unified, composable layer. It extends the data fabric concept by adding native AI capabilities - embedding generation, model serving, retrieval-augmented generation, and reasoning - making intelligence a first-class feature of the data infrastructure rather than a bolt-on.
what is an AI fabricKnowledge Graph Ontology
A knowledge graph ontology is the formal schema that defines the structure of a knowledge graph - the types of entities (classes), their attributes (properties), and the relationships between them. It is the blueprint that turns a raw collection of connected data into a meaningful, queryable, and reasoned knowledge representation.
knowledge graph ontologyRDF vs Property Graph
RDF (Resource Description Framework) and property graphs are the two dominant data models for knowledge graphs. RDF uses a standards-based triple model with global URIs and a rich ecosystem of W3C specifications (OWL, SHACL, SPARQL). Property graphs use a more developer-friendly model with properties on both nodes and edges, queried with languages like Cypher or Gremlin. The choice depends on your priorities: interoperability and reasoning favour RDF; developer simplicity and application-specific use cases often favour property graphs.
RDF vs property graphKnowledge Graph vs Relational Database
A knowledge graph stores data as a network of entities and relationships, making it natural to model and traverse complex, interconnected domains. A relational database stores data in tables with rows and columns, optimised for structured, transactional workloads. They are not competitors but complementary tools - the question is which is the right fit for each use case.
knowledge graph vs relational databaseFIBO (Financial Industry Business Ontology)
FIBO (Financial Industry Business Ontology) is an industry-standard, open-source ontology developed by the EDM Council that provides a formal, machine-readable definition of financial industry concepts - from legal entities and corporate structures to financial instruments, indices, and regulatory requirements. It gives financial institutions a shared vocabulary for data integration, regulatory reporting, and knowledge graph construction.
what is FIBO ontologyOSDU (Open Subsurface Data Universe)
OSDU (Open Subsurface Data Universe) is an open-standard, cloud-native data platform developed by The Open Group for the energy industry. It provides a vendor-neutral framework for storing, managing, and sharing subsurface and operational data - well logs, seismic surveys, production records, and engineering models - using semantic technologies to ensure data is discoverable, interoperable, and reusable across the organisation.
what is OSDUEMMO (Elementary Multiperspective Material Ontology)
EMMO (Elementary Multiperspective Material Ontology) is a top-level ontology for materials science developed under the European Materials Modelling Council (EMMC). It provides a rigorous, physics-based framework for describing materials, their properties, manufacturing processes, and characterisation methods - enabling interoperability across simulation software, experimental databases, and manufacturing systems.
what is EMMO ontologySemantic Infrastructure
Semantic infrastructure is the foundational layer of technologies, standards, and practices that make data machine-understandable across an organisation. It encompasses ontologies, knowledge graphs, taxonomies, metadata management, and semantic integration patterns - the building blocks that enable AI, analytics, and applications to work with data that carries its own meaning rather than relying on brittle, hard-coded mappings.
what is semantic infrastructureContext Graph
A context graph is a knowledge graph specifically positioned as the contextual backbone for AI and application decision-making. The term emphasises the role of graph-structured data in providing the rich, relationship-aware context that large language models, recommendation engines, and intelligent applications need to move beyond keyword matching to genuine understanding.
what is a context graph