Structured knowledge base, Wikimedia project, linked data, items, statements, properties, identifiers, SPARQL queries, multilingual labels, machine-readable facts, CC0 data, and knowledge graph infrastructure

Wikidata

Wikidata is a free, collaborative, multilingual structured knowledge base that stores machine-readable facts used by Wikimedia projects, search systems, apps, researchers, and data tools.

Core idea

Wikidata stores structured data as items, properties, statements, references, labels, and identifiers rather than as ordinary article prose.

Launch

Meta-Wiki describes Wikidata as a Wikimedia project launched in 2012 to create a free knowledge base readable and editable by humans and machines.

License

Wikidata says its data is published under the Creative Commons Public Domain Dedication 1.0, allowing broad reuse.

Wikidata is a structured knowledge base that stores linked facts for Wikimedia projects and other data users.View image on original site

What Wikidata is

Wikidata is a free structured knowledge base in the Wikimedia family. On Wikidata.org, people and software can read, edit, query, and reuse facts about people, places, works, organizations, concepts, events, identifiers, and relationships in a machine-readable form.

Wikidata homepage screenshot showing the search bar, welcome message, free knowledge base description, data entity count, and structured data panels. — Wikidata homepage screenshot showing the free knowledge base interface with search, language controls, data entity count, introduction links, and structured-data learning panels.

Items, properties, and statements

A Wikidata page is usually an item, such as a person, city, book, species, film, or scientific concept. Each item can have labels in many languages, descriptions, aliases, identifiers, and statements. A statement links an item to a property and value, such as a birth date, coordinate location, official website, creator, population, or external database ID.

A knowledge graph for many languages

Wikidata helps avoid repeating the same facts separately across language editions. A single item can connect names, identifiers, and relationships in many languages, making it easier for Wikipedia and other projects to share structured facts while still writing local article prose independently.

Human and machine editing

Wikidata is edited by volunteers, tools, bots, and data imports. That mixture makes it powerful and delicate. Large datasets can improve coverage quickly, but every claim still needs modeling choices, references, constraints, community review, and cleanup when sources disagree or facts change.

Queries and reuse

Developers and researchers use Wikidata through APIs, dumps, entity pages, and SPARQL queries. That makes it useful for data visualization, search enrichment, authority control, catalog matching, digital humanities, linked open data, language tools, and experiments that need structured facts rather than text paragraphs.

Strengths and limits

Wikidata’s strength is that it makes public knowledge computable. Its limits come from uneven coverage, modeling disputes, vandalism, stale values, source quality, identity matching problems, and the difficulty of representing messy reality as clean statements.

Why it matters

Wikidata is one of the web’s most important public knowledge graphs because it connects human-readable projects with machine-readable data. It helps computers answer questions, connect collections, translate labels, identify entities, and reuse open facts without depending entirely on private databases.

Key concepts

Itema Wikidata entity representing a topic such as a person, place, work, concept, or event.
Propertya relationship or attribute used in statements, such as country, creator, population, ISBN, or official website.
Statementa structured claim that connects an item, property, value, qualifiers, and references.
SPARQLa query language used to ask structured questions across Wikidata’s graph.

Common uses

Supplying infobox data, interlanguage links, identifiers, and structured facts for Wikimedia projects.
Connecting museum, library, archive, scientific, and government datasets through shared identifiers.
Building search features, entity recognition systems, maps, timelines, visualizations, and research tools.
Querying public facts about people, places, works, species, organizations, events, and concepts.

Common misconceptions

Wikidata is not Wikipedia in database form; it stores structured claims, not encyclopedia articles.
A claim on Wikidata should not be treated as automatically true without checking references and context.
CC0 data reuse is broad, but users still need judgment about privacy, ethics, source reliability, and downstream effects.
Machine-readable facts can simplify search and analysis, but they can also flatten ambiguity and disagreement.

Open questions

How should Wikidata represent uncertainty, changing facts, disputed identities, and culturally specific knowledge?
Can the project keep quality high while accepting large imports and automated edits?
How will AI systems use Wikidata, and how should they credit or validate its community-maintained data?
What governance model works when libraries, companies, researchers, bots, and volunteers all depend on the same public graph?