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Knowledge Graph

vr.wm-dat-011 · wm-dat-011-knowledge-graph

Graph dataset with ontology, assertions and provenance

World Models Information and virtual systems INF.DAT.KG
Bundle → Layer → Finding → QuestionsClassifiersWhat it isWhy it existsDistinguishing featuresWhat robots and AI may and may not doMoral aspectsOwnersLinks to other meta-modelsIdentity and identifiersDirect propertiesRecognitionCapabilities and actionsHazards and failure modesStandards and interfacesContext of useSources

Bundle → Layer → Finding → Questions Filled

3 bundles · 3 layers · 5 findings · 11 questions

Schema and scope What the graph is about and which vocabulary it uses.

Ontology binding

The ontologies and vocabularies that give the graph meaning.

Bound vocabularies

The ontologies, schemas and versions the graph uses.

  1. Which ontologies or vocabularies, in which versions, does this graph use?
  2. Are there classes or properties in the graph that no bound vocabulary defines?

Graph scope

The domain and coverage the graph claims.

  1. Which domain, entities and period does this graph claim to cover?
  2. Who publishes the graph, and under which licence?
Assertions The statements the graph makes.

Statements and identity

Entities, their identifiers and the facts asserted about them.

Entity identity

How entities are identified and reconciled.

  1. Which identifier scheme does the graph use for entities, and are the identifiers resolvable?
  2. How are duplicate entities detected and merged?

Assertion provenance

Source, method and time of each assertion.

  1. Which source and method produced this assertion, and when?
  2. Is the assertion extracted automatically, inferred or curated by a person?
  3. Which assertions conflict, and how is the conflict recorded?
Quality and release Whether the graph can be trusted and how it changes.

Validation and versions

Shape validation and release history.

Validation status

Results of shape or constraint checks for a release.

  1. Which shape or constraint checks were run on this release, and with what result?
  2. What changed between this release and the previous one?

Classifiers Filled

Family
World Models
Category
Information and virtual systems
Entry kind
standalone-mm
Navigation path
NAV.INF.DAT.KG
Domain
INF.DAT.KG
Industry
Cross-industry
Tags
knowledgegraphinf.dat.kg

What it is Filled

A knowledge graph is a graph dataset of entities and the typed relationships between them, interpreted through an ontology or schema and carrying provenance for its assertions. It is a dataset with semantics; the ontology it uses and the software that stores it are separate things.

Why it exists Filled

Graph dataset with ontology, assertions and provenance

Distinguishing features Filled

  • A knowledge graph is a dataset; the ontology it uses is a model registered separately.
  • Assertions carry provenance, so the graph can say who claimed a fact and how it was derived.
  • Differs from a relational dataset by typed links between identified entities that can cross sources.
  • Distinct from the graph database software that stores it.

What robots and AI may and may not do Filled

Must not

  • Add assertions without provenance or present inferred facts as curated ones.
  • Merge entities about people on weak matches without review.
  • Assert sensitive facts about identifiable people beyond the graph's lawful purpose.
  • Silently change the meaning of a bound ontology term in place.
  • Republish the graph against its licence.

Only with a human decision

  • Approving changes to the ontology bound to the graph.
  • Accepting merges of entities that describe people.
  • Publishing a release with personal or sensitive data.

May

  • Query the graph within its licence and access conditions.
  • Propose new assertions with source, method and confidence recorded.
  • Run shape validation and report violations.
  • Flag conflicting or unsourced assertions for curation.

Moral aspects Filled

  • Linking data about people across sources can reveal more than any source did alone.
  • Errors propagate quickly when many systems and AI agents treat the graph as ground truth.
  • Bias in sources and extraction shapes what the graph says about groups and places.

Who is affected

  • People described in the graph
  • Publishers and curators of the graph
  • Systems and users that rely on its assertions

Owners Filled

Steward

The data steward or knowledge engineer who answers for the graph's content, scope and releases.

Master systems

  • Graph database or triple store
  • Data catalogue
  • Ontology registry

Links to other meta-models Filled

parent

  • WM-KNW-001

What else AI and robots need to interact with it Filled

Identity and identifiers required Filled

  • A graph is identified by a persistent identifier or dataset URI with a release version.
  • Entities inside it are identified by IRIs, often linked to external authority identifiers.

Direct properties not applicable Not applicable

Not applicable

A knowledge graph is information, not a physical object; size, coverage and quality figures are dataset metadata recorded in the structure.

Recognition optional Filled

  • Marked by typed links between identified entities and a declared ontology or schema.
  • Often confused with the ontology alone, with a graph database product or with a plain linked dataset.

Capabilities and actions required Filled

  • Answers queries that follow relationships across entities and sources.
  • Supports inference from ontology axioms where a reasoner is used.
  • Supports validation of structure against declared shapes.

Hazards and failure modes required Filled

  • Wrong merges of entities spread errors across every linked fact.
  • Re-identification of people from combined assertions.
  • Unsourced assertions mistaken for verified knowledge.

Standards and interfaces required Filled

  • W3C RDF 1.1 and SPARQL 1.1 for data and queries.
  • W3C OWL 2 and SKOS for ontologies and vocabularies.
  • W3C SHACL for shape validation and PROV-O for provenance.
  • ISO/IEC 39075 GQL for property graph queries.

Context of use required Filled

  • Used for search, data integration, research and grounding of AI systems.
  • Personal data in the graph falls under data protection law such as the GDPR.

Sources Filled

  1. RDF 1.1 Concepts and Abstract Syntax, W3C Recommendation
  2. Shapes Constraint Language (SHACL), W3C Recommendation
  3. Knowledge Graphs, Hogan et al., ACM Computing Surveys, 2021

Open questions

  • Planned model: boundary questions, research and every section remain to be written.

Machine files

Card as JSON Specification AGENTS.md Card backlog vercy.card/1

Provenance

planned (registry candidate) · todo

Built from: models/runtime-index.json, ver-cy/world-models/card-supplements/wm-dat-011-knowledge-graph.json

Planned entry, hidden from the catalogue until researched.