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FAIR Principles

The FAIR Principles provide a set of guiding goals for scientific data management:

  • Findable – Data and metadata should be easy to find, with rich metadata and unique persistent identifiers.
  • Accessible – Data should be retrievable via standardized protocols, with clear access conditions.
  • Interoperable – Data should use formal, shared vocabularies and reference other data.
  • Reusable – Data should be richly described with clear provenance and licensing for reuse.

FAIR and STAMPED are complementary. FAIR describes what good data management looks like from the consumer’s perspective, while STAMPED focuses on the engineering practices that help achieve those goals from the producer’s perspective. A project that follows STAMPED principles will naturally tend toward FAIR compliance, because practices like version control, structured metadata, provenance tracking, and standardized organization directly support findability, accessibility, interoperability, and reusability.