Introduction to the Semantic Web

The Semantic Web extends the current web so that data can be understood by machines as well as by humans.
The book Foundations of Semantic Web Technologies presents the conceptual foundations and the W3C standards
for representing knowledge and enabling automated reasoning.

Main Technologies

RDF (Resource Description Framework)

A triple model (subject–predicate–object) forming the basis of knowledge graphs.
➜ RDF at W3C

RDFS (RDF Schema)

Adds schemas and hierarchies (classes, subclasses, properties) to enrich RDF data.

OWL (Web Ontology Language)

Language for defining complex ontologies based on description logics, enabling interoperability and
semantic validation. ➜ OWL 2 Overview

SPARQL

Query language to interrogate RDF data, including inferences.
➜ SPARQL 1.1

Reasoning and inference

Based on ontologies, reasoning engines can deduce new knowledge and check consistency
(e.g., “all cats are mammals” + “Misha is a cat” ⇒ “Misha is a mammal”).

Applications and Use Cases

• Digital libraries: semantic search and metadata harmonization.
• Enterprises: corporate knowledge management and data integration.
• Bioinformatics and recommender systems: heterogeneous data and contextualized results.

➜ Explore also the Linked Open Data cloud.

Related reading:
Introduction to NLP,
Semantic Search,
Knowledge Graphs.

Conclusions

The core of the Semantic Web is built on RDF, RDFS, OWL and SPARQL. Ontologies and
automatic reasoning provide meaning and guarantees to data. The future combines these standards with
AI and knowledge graphs for intelligent applications at scale.