Specifications#

Welcome to the FAIR Data JSON Schema Specifications. This section provides the authoritative technical reference for the fair: metadata keywords, keyword scopes, dataset structures, and AI/machine-actionable interfaces.


Specification Overview#

FAIR Data JSON Schema extends JSON Schema (Draft 2020-12) by defining machine-actionable annotation keywords prefixed with fair:. These keywords allow Information Technologists (developers, data engineers, AI/ML experts) and Data Practitioners (data stewards, scientists, researchers) to embed rich metadata directly into standard technical validation schemas.

🔑 Keyword Reference

Complete reference of all fair: keywords organized by Universal, Dataset, and Property scopes.

Keyword Reference & Scopes
🤖 AI & Machine Actionability

Learn how fair: metadata natively feeds into LLMs, function calling, and the Model Context Protocol (MCP).

Background & Motivation
🌐 CDIF v1.1 Alignment

Detailed mapping between FAIR Data JSON Schema properties and Cross-Domain Interoperability Framework profiles.

Alignment with CDIF v1.1 Profiles & FAIR Data JSON Schema

Scope Architecture#

To support simple flat files as well as complex hierarchical data products (such as censuses or multi-table research packages), metadata keywords are organized into three functional scopes:

  1. Universal Scope: Identifiers (fair:label, fair:description, fair:conceptRef, fair:resourceType) applicable to any object level.

  2. Dataset Scope: Container-level metadata (fair:contributors, fair:licenseRef, fair:temporalCoverage, fair:structureType, fair:quality) describing provenance, rights, and spatial-temporal bounds.

  3. Property Scope: Field-level metadata (fair:measurementUnitRef, fair:classificationRef, fair:sentinel, variable cascade references) describing data representations and statistical concepts.


Machine Actionability & Zero Lock-In#

Because standard JSON Schema engines ignore unrecognized keywords, adding fair: annotations creates zero breaking changes for existing software pipelines:

  • Standard JSON Schema Validators: Execute data payload validation normally while ignoring fair: annotations.

  • AI Agents & MCP Servers: Read fair: annotations to infer unit conversions, column meanings, and missing data sentinel codes automatically.

  • Data Practitioners & Stewards: Produce machine-enforceable metadata records using the JSON tools tech teams already use every day.


Advanced Extension Mechanisms#

For technical architects who wish to extend or customize the meta-schema itself using custom $vocabulary declarations, custom $schema dialects, or JSON Schema Draft 2020-12 meta-schemas:

👉 Extension Mechanisms (Advanced Users)