Knowledge graph
information repository structured as a graph of entities and relationships
In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the free-form semantics or relationships underlying these entities.
Since the development of the Semantic Web, knowledge graphs have often been associated with linked open data projects, focusing on the connections between concepts and entities. They are also historically associated with and used by search engines such as Google, Bing, and Yahoo; knowledge engines and question-answering services such as WolframAlpha, Apple's Siri, and Amazon Alexa; and social networks such as LinkedIn and Facebook.
Recent developments in data science and machine learning, particularly in graph neural networks, representation learning, and machine learning, have broadened the scope of knowledge graphs beyond their traditional use in search engines and recommender systems. They are increasingly used in scientific research, with notable applications in fields such as genomics, proteomics, and systems biology.
History
In December 1968, the Human Resources Research Organization (HumRRO) delivered a presentation for the Society for General Systems Research's Annual Meeting in which they described the "Subject-Matter Map," and formalized the idea of representing knowledge as a graph. In 1972, the Austrian linguist Edgar W. Schneider cited HumRRO's presentation in his discussion of how to build modular instructional systems for courses, and coined the term "Knowledge Graph." In the late 1980s, the University of Groningen and University of Twente jointly began a project called Knowledge Graphs, focusing on the design of semantic networks with edges restricted to a limited set of relations, to facilitate algebras on the graph. In subsequent decades, the distinction between semantic networks and knowledge graphs was blurred.
Some early knowledge graphs were topic-specific.
The public source identifies “Knowledge graph” as information repository structured as a graph of entities and relationships. This brief keeps that definition visible, then builds a research path around Knowledge, graph and information.
Why this record matters
A short description can identify a subject without explaining its stakes. For “Knowledge graph”, the useful work is to connect “information repository structured as a graph of entities and relationships” to the records capable of establishing context and consequence.
The citation trail is more important than the brevity of the summary: it shows where individual claims can be examined in context. The source revision retrieved here is dated Sep 21, 2026. The linked authority identifier is Q33002955. 1 of 1 selected statements include explicit references; 0 carry qualifiers and 0 use preferred rank. The first chronological checks are 1968 and 1972.
The absence of detail may reflect summary conventions rather than a lack of surviving documentation. The lead is largely declarative, so disagreement and counter-evidence require a deliberate search beyond the opening account. Authority statements aid reconciliation but still require their own references, qualifiers and ranks to be checked.
How to read it
Use the entry as an orientation point, then follow its citations and revision history. Names, dates and institutional relationships should be checked against the original record.
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The closest primary source, responsible institution and strongest cited specialist reference.
Three-step research path
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- Expand the search: follow Knowledge graph primary sources, Knowledge graph archive and Knowledge research across catalogues and specialist indexes.
- Test the account: compare the strongest cited source with the responsible institution’s current record and note any disagreement.
Questions for further research
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This entry incorporates text from “Knowledge graph” on English Wikipedia. Contributors are listed in the page history. Text is available under the Creative Commons Attribution-ShareAlike 4.0 License. Selected authority identifiers and statements are retrieved from Wikidata under CC0; their references and qualifiers remain part of the verification path.