New to FAIR data? Here's what you need to know...

In today’s data-driven world, organisations are collecting more information than ever — but unless that data can be found, shared, and reused safely, it quickly loses value. That’s where FAIR data comes in.

What Is FAIR Data?

FAIR stands for Findable, Accessible, Interoperable, and Reusable.

Introduced in 2016, the FAIR principles provide a framework for making data more useful, transparent, and shareable. Originally adopted in research and science, FAIR data is now recognised globally as best practice in data management across academia, government, and business.

Why Does FAIR Data Matter?

FAIR data helps people and organisations get real value from their information. It has clear, real-world implications — from saving lives to informing national policy.

For researchers

FAIR data ensures users can share and build on each other’s work more effectively. With well-described, discoverable datasets, researchers can:

• Quickly find relevant data rather than sifting through irrelevant information

• Cite datasets properly

• Avoid duplicating existing studies

• Improve reproducibility and speed up discovery

For companies and governments

FAIR data enables an environment of trust, standardisation, and control, making safe collaboration possible across systems. It allows departments, agencies, and private partners to:

• Share information securely

• Reduce duplication

• Make decisions based on consistent, high-quality data

Is FAIR Data a Legal Requirement?

While the term “FAIR data” doesn’t appear directly in UK law, many of its principles are embedded in recent legislation, including the UK Data (Use and Access) Act 2025. This Act modernises how data is managed and shared, incorporating FAIR-aligned elements such as:

• Interoperability standards

• Data access rights

• Clear governance structures

In practice, UK organisations will increasingly need to align with FAIR principles to remain compliant, participate in new data-sharing frameworks, and maintain trust with partners.

Breaking Down the FAIR Data Principles

Findable — clear visibility and traceability

• Assign each dataset a unique identifier (e.g., DOI or dataset ID).

• Provide rich, searchable metadata describing what the data is and how to use it.

Accessible — secure, governed data exchange

• Make data and metadata retrievable via standard protocols (e.g., APIs, HTTP).

• Define clear access conditions (open, restricted, or request-based).

• Ensure metadata remains visible even if the data itself is restricted.

Interoperable — different systems speak the same language

• Use standard formats and controlled vocabularies recognised in your field.

• Link metadata to related datasets using shared identifiers.

• Ensure data can move smoothly across platforms, disciplines, and technologies.

Reusable — trust and shared understanding

• Include clear licensing and usage terms.

• Document data provenance (who created it, how, and when).

• Follow community standards to support reproducibility and verification.

How to Make Your Data FAIR

At MetadataWorks, we help organisations unlock the full potential of their data by making it FAIR.

Our data catalogue and expert support guide you through managing metadata, ensuring compliance, improving efficiency, and enabling trusted data sharing across teams and partners.

Whether you’re enhancing data governance, building new data products, or preparing for the UK Data (Use and Access) Act, our team can help you make your data FAIR — safely and efficiently.

Get in touch: hello@metadataworks.ai