What is Wikidata?

Wikidata is a structured knowledge base run by the Wikimedia Foundation, the nonprofit behind Wikipedia. Where Wikipedia holds prose articles, Wikidata holds facts in a fixed format that software can read.

Every thing it describes is an item, a single entity with a unique identifier that starts with Q. Douglas Adams, for example, is Q42. Each item carries statements: a property (identified by a P number, such as "founded by" or "headquarters location"), a value, and optional qualifiers and references.

Linked together, those statements form one of the largest public examples of a knowledge graph: a network of entities and the relationships between them.

Wikidata is open in two senses. Anyone can edit it, with or without an account. Its structured data is released under a public domain dedication (CC0), so anyone can reuse it, including commercial software.

Openness comes with rules that volunteer editors enforce:

• Notability. An item needs a reason to exist: a link to a Wikimedia project such as a Wikipedia article, a clearly identifiable entity described in serious public sources, or a structural need inside Wikidata itself.
• Verifiability. Statements should cite references. Unsourced claims are easier to challenge and remove.
• Neutrality. Wikidata records facts, not marketing. Promotional edits tend to be reverted, and editing an item about your own employer is a conflict of interest that editors watch for.
• Shared ownership. No company owns its item. Other editors and bots can change any statement at any time.

If your company already has an item, the useful move is a careful audit, not a rewrite. The Wikidata hygiene playbook walks through checking each statement.

Wikidata is widely reused open data, which is why marketers ask about it. The honest answer depends on which stage of an AI answer you mean.

• Parametric (training). A model may have seen Wikidata during training. Vendors do not disclose how much, or what weight it carries. Nothing a company edits today reaches an answer given with search off until a future model is trained.
• Retrieval (search on). When an engine searches the web, a Wikidata page is one possible source among many. Engines do not document treating it specially. The difference is covered in search on vs search off answers.

The broader evidence is cautious. A July 2026 critical survey of 45 GEO studies (arXiv 2607.14035) found that no reviewed technique shows a stable, cross-platform causal effect on discoverability. No study in our evidence base measures Wikidata at all.

So treat Wikidata as a place to check for wrong facts, not as a lever. A stale dissolution date or a merged item about a similarly named firm is worth fixing on its own merits, and it is one thing to rule out when AI says your company closed. For the full question, see does my Wikidata entry affect what AI says.

• "A Wikidata entry gets you cited by AI." No published evidence supports this. Anyone selling it as a citation tactic is making a claim nobody has measured.
• "Wikidata is the same as Wikipedia." They are sister projects. Wikipedia articles link to Wikidata items, but many items have no article. See whether you need a Wikipedia page.
• "Wikidata is Google's Knowledge Graph." It is a separate, public project. Google says AI Overviews and AI Mode need no special optimization beyond being indexed and eligible for a snippet.
• "My item is my profile." It is community-edited. You can propose corrections with references, but you cannot lock it.
• "More statements mean more visibility." Statement count is not a documented signal. Accuracy and references matter more than volume.

• Entity: the person, company, place or concept a Wikidata item describes.
• Knowledge graph: the structure Wikidata's linked statements form.
• Brand conflation: when AI mixes up two companies, sometimes traceable to confused or merged records in public data.