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Research data management: a practical guide

FAIR data

A practical guide to help you manage your research data well, covering best practice for the successful organisation, storage, documentation, archiving and sharing of research data.

FAIR

FAIR data is Findable, Accessible, Interoperable and Reusable

The FAIR Data Principles are useful guidelines for sharing data in a way that will enhance reusability.

stick men representing FAIR - Findable, Accessible, Interoperable and Reusable - data

If you plan to share some of your research data, whether openly or with access restrictions, your data should be made as discoverable and reusable as possible. Working towards making your research data FAIR is a simple way to do this.

FAIR data

Making your data FAIR
 

magnifying glass

Findable

Metadata and data is easy to find, by both humans and machines.

 

Deposit your research data in a trusted or discipline-specific data repository, where you'll be required to provide relevant metadata and the repository will assign a persistent identifier (e.g. a Digital Object Identifier (DOI)) to your data. Your data and metadata will then be searchable and discoverable online. Your shared data is also easier to find and cite when it has a DOI.

Include the DOI for the dataset in the data access statement of associated published outputs.

keyAccessible

Once found, humans and machines can access the data and/or metadata. 


Deposit your research data in a trusted or discipline-specific data repository, it will have standard protocols in place to support online retrieval. 

Where data cannot be shared openly, the metadata record should be openly available and should detail the conditions under which the data may be accessed. 

Interoperable

Data can be integrated with other data and is compatible with applications or workflows for analysis, storage and processing.

 

Use well-known and preferably open file formats (and software) to enable others to more easily access and reuse your shared data. Ensuring your data is well structured will also enable its reusability.

Make use of standards for metadata and community agreed schemes, vocabularies, keywords, ontologies where these exist.

Reusable

Metadata and data is well-described, and data can be replicated and/or combined.

 

Provide documentation with your shared data, to enable others to understand it.

Link your shared data to its associated published outputs, to provide the contextual information needed to make sense of it. This can be achieved in PURE.

Assign a licence to your shared data, to clarify the terms of its use.

Check how FAIR your research data is using the FAIR Data Self Assessment Tool, a tool provided by the Australian Research Data Commons.

Open and FAIR data

Open data "can be freely used, modified, and shared by anyone for any purpose." - The Open Definition

To be fully open, research data must also be FAIR. However, data can be FAIR without being open.

There are many good reasons why data may not be shared openly. In such circumstances, you should still aim to make data FAIR by making the metadata record openly available and including details of the conditions under which the data may be accessed.

The University supports both open and FAIR data in its data repository, Research Data York.