Origins
The Semantic Web: the original vision
The Semantic Web asked a simple but difficult question: what would the web become if computers could process the meaning of information, not just display documents?
A web of data, not only documents
The ordinary web made documents easy to publish and link. The Semantic Web proposed a deeper layer: data that carried explicit meaning. Instead of relying on a person to interpret a page, software could identify entities, properties, relationships, and rules.
This did not require replacing the web. It required adding structured descriptions to it. A page about a book could state that the book has an author, publication date, subject, identifier, and publisher. Those statements could then be linked to other statements across the web.
RDF, triples, and ontologies
RDF, the Resource Description Framework, represents information as graph-like statements. A common teaching form is the triple: subject, predicate, object. For example: Wikidata → is a → knowledge base. Many triples together create a web of connected meaning.
Ontologies add controlled vocabularies and formal relationships. They help systems distinguish types of things, properties of things, and rules about how those things can be related. OWL, the Web Ontology Language, was designed for applications that need to process content rather than only present it.
Why the vision was hard
The Semantic Web required agreement on vocabularies, identifiers, data quality, publication practices, and incentives. Those are social problems as much as technical problems. It is easier to publish a page than to maintain a clean ontology with trustworthy links.
Even so, the idea survived in many practical forms. Linked data, Schema.org markup, Wikidata, enterprise knowledge graphs, library metadata, digital-object identifiers, and AI retrieval systems all inherit part of the same ambition: make meaning more explicit and reusable.
Internal links
To see how this vision became a public knowledge infrastructure, read Wikipedia, Wikidata, and Public Knowledge. For its applied form in search and data systems, read Knowledge Graphs and Structured Meaning.