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.

What is a FAIR vocabulary?

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:

• Findable: be registered (indexed, listed) in a vocabulary service
• Accessible: be available on the web, downloadable
• Interoperable: encoded in a standard representation, such as the Web Ontology Language (OWL) or SKOS and domain-specific extensions
• Reusable: licensed and maintained, ideally with an open license

FAIR vocabularies representation relies on web standards

Guidelines for FAIR Vocabularies

• Guidelines for making a vocabulary FAIR
• Guidelines for maintaining a FAIR vocabulary - coming soon!