FAIR Data Cookbook#
Welcome to the FAIR Data Cookbook! This collection of recipes provides practical, step-by-step guides for implementing the FAIR Data JSON Schema vocabularies in your data assets with minimal effort.
Each recipe addresses a specific task—from basic identification to advanced semantic mapping—and includes working code examples you can copy and adapt immediately.
🟢 Tier 1: Essential Recipes (Start Here)#
Get started in minutes using simple, intuitive annotations for everyday datasets:
Annotate a simple, single-table dataset with title, license, unit type, measurement units, and self-documenting codes.
Document primary canonical identifiers ($id, $anchor), resolvable PIDs (DOIs, w3ids, DIDs), random GUIDs, and scoped secondary IDs.
Learn how to evolve standard JSON Schema enum fields into self-documenting FAIR coded values mapped to human titles and web concepts.
Learn how to write multilingual titles, labels, descriptions, and coded values using BCP-47 language maps.
🔵 Tier 2: Advanced & Extended Recipes (Optional Deep-Dive)#
For users who want to dig deeper into formal data stewardship, these advanced recipes explore deep provenance, population bounds, and complex data lineage:
Learn how to annotate basic dataset schemas and describe tables and resources with minimal effort.
Implement formal variable lineage (Instance -> Represented -> Conceptual) using internal and external schema references.
Describe complex multi-table data products, hierarchical structures, and cross-dataset join relationships.
Explore the four core mechanisms used to extend JSON Schema: Annotations, Vocabularies, Dialects, and Refinements.
All Recipes#
[!TIP] Each recipe includes a “How-to” section with actionable steps. Check out the
examples/folder in the source repository for complete JSON schema files.