Studio / Area

Context & Knowledge

Make the information and concepts a system relies on explicit.

What does the system need to know, and how is that knowledge made explicit?

In scope

  • Vocabularies, schemas, rules, entity identity, metadata, and provenance representations

Boundary

  • Data ingestion and cleaning; operational oversight and approval

Start with the outcome

Functions

Function

Decision modeling

Describe decision requirements and logic using explicit diagrams or tables.

Function

OpenLineage

Open specification for metadata about data-processing jobs, runs and datasets.

Function

SKOS

Vocabulary for sharing concept schemes, labels, and semantic relationships.

Function

Define a shared vocabulary

Give recurring concepts stable names and relationships so people and systems interpret them consistently.

Function

Author an ontology

Define and revise formal domain concepts, relations, and constraints.

Function

Ontology entailment

Apply defined RDF/OWL semantics to derive implied statements from graph facts.

Representative paths

Methods and options

standard

SKOS

Vocabulary for sharing concept schemes, labels, and semantic relationships.

approach

Decision modeling

Describe decision requirements and logic using explicit diagrams or tables.

standard

OpenLineage

Open specification for metadata about data-processing jobs, runs and datasets.

approach

Ontology entailment

Apply defined RDF/OWL semantics to derive implied statements from graph facts.

Across the Studio

Governance connection

Provenance can be represented here while its retention and use for assurance are governed elsewhere.

Related records

Sources

  1. AI Studio methodologyCameron Smith · checked 2026-09-29

Last reviewed 2026-09-29