Cross-discipline data discovery, integration, and synthesis remain challenging tasks for technical, social and content-related reasons. However, those tasks are crucial for addressing global scientific and societal challenges. Understanding the data, identifying the terminology used to annotate them, and how they relate is a prerequisite to enable data integration.
Here we provide a series of guidelines that help on creating and using FAIR (Findable, Accessible, Interoperable & Reusable) vocabularies.
The FAIR guiding principles for scientific data management and stewardshipt provide recommendations to make data Findable, Accessible, Interoperable and Reusable.
One of the principles indicate that to be interoperable:
I2. (meta)data use vocabularies that follow FAIR principles
In this project we provide guidance for FAIR vocabularies, which are crucial to producing FAIR data.
For a vocabulary to be FAIR, it should be:
FAIR vocabularies representation relies on web standards