What is Wikidata?
Wikidata is a free, collaborative, multilingual knowledge base that supports Wikipedia and stores facts about entities as structured statements anyone can read and reuse. Wikidata is where Wikipedia's facts live as data: one item per thing, with statements anyone can read and reuse. Its CC0 license means search engines, AI developers and anyone else may use it without restriction.
How does Wikidata work?
Wikidata describes itself as a free, collaborative, multilingual, secondary knowledge base that supports Wikipedia and other Wikimedia projects, with data entered and maintained by its editors (Wikidata: Introduction, last edited July 31, 2026).
Each item has a label, a description and aliases, and an ID made of a Q and a number; Douglas Adams is Q42. Properties carry a P and a number, such as educated at (P69). A statement pairs a property with a value, and statements can carry their sources.
Why does Wikidata matter for brands?
Because it is open, structured and reused. Wikidata states its data is published under the Creative Commons Public Domain Dedication (CC0), so it can be copied into other databases and products freely.
That makes an accurate item a cheap way to state your core facts once, in a form machines read, with sources attached. An inaccurate one spreads errors the same way.
What does this look like in a real example?
Wikipedia, which Wikidata supports, is one of the most cited sites in AI answers. In the public Tesla example (Oct 4, 2026), en.wikipedia.org was cited 24 times across buyer and brand questions, and it was Claude's most cited site, 16 times on 25 buyer questions.
For a brand like Tesla, the reference record engines lean on is maintained by volunteers, not by the company. The same holds for any brand with an item: you can propose corrections with sources, but you do not own the page.
Should your brand have a Wikidata item?
Only if it meets Wikidata's own notability rules; read them before creating anything. If it does:
- Keep statements factual and sourced: official website, founding date, headquarters, industry.
- Link the item to your official profiles through their identifier properties.
- Disclose a connection to the company when you edit, and prefer proposing changes with sources.
- Check the item when your facts change, such as a new name or headquarters.
Does Proofsource check Wikidata?
Yes. Proofsource's profile audit checks whether you have a consistent listing on Wikidata alongside G2, Capterra, Crunchbase, LinkedIn, Product Hunt and other directories, and flags the ones that are missing or disagree with your site. See Accuracy and identity.
Common questions about Wikidata
Is Wikidata the same as Wikipedia?
No. Wikipedia holds articles; Wikidata holds structured facts that Wikipedia and other projects draw on. A company can have a Wikidata item without a Wikipedia article.
Who can edit Wikidata?
Anyone, under its policies. Edits are visible and reversible, and unsourced or promotional changes are often removed.
Do AI engines use Wikidata?
Its data is free to reuse and widely copied, but engines do not publish exactly how they use it. Wikipedia, which it supports, is among the most cited sites in AI answers.
What is a QID?
Wikidata's ID for an item: Q followed by a number, such as Q42. It identifies the thing itself, independent of its name in any language.
Related terms
- Knowledge graph
A knowledge graph is a database of entities and the facts that connect them, and Google's Knowledge Graph is the best-known one, with millions of entries about people, places and things.
- Entity
In search and AI, an entity is one distinct, identifiable thing, such as a company, product, person or place, that a system can recognize and keep apart from things with similar names.
- Schema markup (structured data)
Schema markup, or structured data, is code on a page, usually JSON-LD using the schema.org vocabulary, that states facts about the page and its subject in a form machines can read.
- Third-party sources
Third-party sources are pages about your category written by someone other than you, such as reviews, roundups, forum threads, videos and competitors' sites, that AI engines read and cite.
Worked example: Tesla, public AI answers, Oct 4, 2026: Proofsource's first scan of Tesla, 25 buyer questions and 5 brand questions, one answer per question on each of four engines. A small sample from one brand, shown as an example, not a benchmark.
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