---
slug: what-is-semantic-web
title: What Is the Semantic Web
canonical: https://miscsubjects.com/a/what-is-semantic-web
---

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# What Is the Semantic Web

## §SELF — what-is-semantic-web

**What this page is:** A description of the Semantic Web vision, its technologies, and why it did not achieve wide adoption.
**What it explains:** RDF, RDFS, OWL, SPARQL, JSON-LD, and Linked Data principles.
**Why read it:** To understand how machine-readable data on the web works, why the original vision stalled, and how large language models change the equation.

### What the Semantic Web Is

The Semantic Web is Tim Berners-Lee's vision (first articulated in a 2001 Scientific American article, then formalized through W3C standards from 2001 to 2010 and beyond) of a web where data is machine-readable, not just human-readable. The core proposition: web pages should contain structured, labeled data that software can parse, reason about, and connect automatically.

### Why It Matters

The web as originally built contains pages (documents) linked by hyperlinks. Humans read the pages and understand the links. Machines can fetch pages and follow links, but they cannot understand what the content means. The Semantic Web attempted to solve this by adding semantic annotations — labels that say "this string is a person's name" or "this number is a price." Search engines partially adopted this (Google Rich Snippets, Facebook Open Graph). The broader vision — a global graph of interconnected, machine-understandable data — never reached critical mass because there was no general-purpose consumer that could traverse and use the graph.

### The Key Idea

The Resource Description Framework (RDF) is the data model. Every piece of information is a triple: subject-predicate-object. Example: `<Alice> <knows> <Bob>` or `<Alice> <age> "30"`. Each element in a triple is identified by a URI (Uniform Resource Identifier), a global identifier analogous to a URL but for things rather than pages. A collection of triples forms a directed graph: subjects and objects are nodes, predicates are labeled edges. Programs can traverse this graph by following edges from node to node.

RDF Schema (RDFS) adds a vocabulary for defining types (`rdfs:Class`) and properties (`rdfs:Property`), and relationships like `rdfs:subClassOf` (one type is a subset of another).

OWL (Web Ontology Language) extends RDFS with logical constructs: you can state that a property is transitive (if A is-connected-to B and B is-connected-to C, then A is-connected-to C), or that two classes are disjoint (nothing is both a Mammal and a Reptile). OWL reasoners can infer new triples from existing ones.

SPARQL is a query language for RDF graphs. It resembles SQL but operates on triple patterns. You ask for all bindings of variables that match a set of triple patterns in the graph.

JSON-LD (JavaScript Object Notation for Linked Data) is a way to embed RDF triples inside ordinary JSON objects using `@context` to map keys to URIs. It allows web APIs to serve semantic data without requiring consumers to understand RDF explicitly.

### What They Got Right

**Linked Data principles (Berners-Lee, 2006).** Four rules: (1) Use URIs as names for things. (2) Use HTTP URIs so those names can be looked up. (3) When someone looks up a URI, provide useful information (using RDF, SPARQL, etc.). (4) Include links to other URIs so more things can be discovered. These principles are sound and underpin modern API design, even where RDF is not used.

**The graph model.** Representing knowledge as a graph (nodes connected by labeled edges) is the correct abstraction for many types of data. Graph databases (Neo4j, Amazon Neptune) and knowledge graphs (Google Knowledge Graph, Wikidata) use this model successfully.

**JSON-LD as a bridge.** JSON-LD achieves interoperability: existing JSON parsers can read it, and RDF tools can extract semantic triples from it. It is the most widely adopted Semantic Web technology in practice.

**Wikidata.** A collaborative knowledge base of over 100 million items, each with a URI, described in RDF. It is the largest working implementation of the Semantic Web vision.

### What They Got Wrong or Left Unfinished

**No consumer application.** The Semantic Web built a data infrastructure but never created the application that would make that infrastructure valuable to end users. Without a reason to publish structured data, publishers did not. This is a chicken-and-egg problem: no data means no applications, no applications means no incentive to publish data.

**OWL was too complex.** The full OWL language (OWL 2 DL) is undecidable in some profiles — meaning a reasoner might run forever on certain inputs. Simpler subsets were defined but the complexity discouraged adoption.

**The ontology construction bottleneck.** Building accurate, shared ontologies (agreed-upon vocabularies for a domain) requires domain experts, logicians, and ongoing maintenance. Most organizations could not afford this effort.

**Assumed publishers would annotate.** The vision required content creators to add semantic markup manually. In practice, most publishers do not. Automated extraction (parsing natural language, scraping tables) turned out to be more scalable.

### How It Connects to Other Ideas

**Knowledge graphs.** Google's Knowledge Graph, Wikidata, and enterprise knowledge graphs are direct descendants of the Semantic Web. They use the RDF graph model but typically simplify or bypass OWL reasoning in favor of direct query and embedding-based methods.

**Schema.org.** A collaborative vocabulary (founded by Google, Microsoft, Yahoo, and Yandex) for annotating web pages. It uses the Semantic Web stack (RDF, JSON-LD) but restricts the vocabulary to a manageable set of types and properties. It is the most successful practical application of Semantic Web technology.

**Large language models.** An LLM can parse text, extract entities and relationships, and traverse linked data. It is the first general-purpose consumer that can take a URI, fetch the data at that URI, interpret it in context, and follow links to other URIs. This addresses the original missing-consumer problem.

**Linked Open Data.** A project to publish existing open datasets (government data, scientific data, cultural heritage) as RDF on the web. DBpedia (structured data extracted from Wikipedia) is the largest Linked Open Data source.

### Sources

Berners-Lee, T., Hendler, J., & Lassila, O. (2001). "The Semantic Web." *Scientific American*, 284(5), 34-43.

Berners-Lee, T. (2006). "Linked Data — Design Issues." W3C. https://www.w3.org/DesignIssues/LinkedData.html

W3C. (2014). "JSON-LD 1.0." W3C Recommendation. https://www.w3.org/TR/json-ld/

W3C. (2012). "OWL 2 Web Ontology Language Document Overview." W3C Recommendation. https://www.w3.org/TR/owl2-overview/

Hogan, A. et al. (2021). *Knowledge Graphs*. Morgan & Claypool.

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## Up the tree

- [OIP root](https://miscsubjects.com/a/oip) — protocol root, zero-context entry
- [Thinker Reference hub](https://miscsubjects.com/a/oip-thinker-reference) — full hierarchy map
- [Protocol Concepts shelf](https://miscsubjects.com/a/oip-protocol-concepts) — siblings on this shelf
- [Voxel graph article](https://miscsubjects.com/a/what-is-voxel-graph) — how pages link as voxels
- [Self-describing protocol](https://miscsubjects.com/a/what-is-self-describing-protocol)

## Related on this shelf

- [What Is Autopoiesis](https://miscsubjects.com/a/what-is-autopoiesis)
- [What Is Capability-Based Security](https://miscsubjects.com/a/what-is-capability-security)
- [What Is a Capability Token](https://miscsubjects.com/a/what-is-capability-token)
- [What Is a Confused Deputy](https://miscsubjects.com/a/what-is-confused-deputy)
- [What Is Context as Cursor](https://miscsubjects.com/a/what-is-context-as-cursor)
- [What Is a Convergence Catalogue](https://miscsubjects.com/a/what-is-convergence-catalogue)
- [What Is a Falsification Surface](https://miscsubjects.com/a/what-is-falsification-surface)
- [What Is HATEOAS](https://miscsubjects.com/a/what-is-hateoas)

## Machine surfaces

- Public page: `https://miscsubjects.com/a/what-is-semantic-web`
- JSON article: `https://miscsubjects.com/api/articles/what-is-semantic-web`
- OIP ask: `https://miscsubjects.com/api/dispatch?ask=What%20Is%20the%20Semantic%20Web`


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## Where OIP does this differently (required edge)

OIP difference: machine-readable operations without requiring a global ontology committee — local object contracts + registry.

