What are FAIR data principles?

IOTICS has the tools to make your data FAIR, but what does it actually mean?

Educational 27 Oct 2021 by Jane Edwards

Findable, Accessible, Interoperable, and Reusable. Those are the data principles articulated by a group of scientists and organisations in 2016 and published in Scientific Data. The group would go on to  form the self-governed initiative, GOFAIR. Their mission was to encourage an open and inclusive digital ecosystem for individuals, institutions and organisations. GOFAIR was formed to support those communities who are actively trying to implement the FAIR data principles. 

The FAIR data principles are an approach that should be applied to data throughout its lifecycle. They are closely linked and build upon each other to ultimately achieve the goal of machine actionability, because “humans increasingly rely on computational support to deal with data”.

FAIR data is commonly mistaken as being open data, however, the two are not the same. Simply, open data is data that can be freely used and modified by anyone with an internet connection and for any purpose. FAIR data on the other hand sets out practices that respect legal and contractual requirements and may require authorisation to be accessed to protect intellectual property and personal information. 

IOTICS and FAIR data

IOTICS believe that the FAIR data principles can be applied to digital twins, supporting the twins’ ability to interoperate. The vision of reusable digital twins has been present from our founding, enabling use cases to evolve over time, exchange insights, and building solutions that have not yet been imagined, let alone specified.

Imagine if digital twins could be used for any purpose, by any application and even found and accessed (if authorised) on the web by a typical browser model. Digital twins of assets are enabled to interact across ecosystems of partners and organisations. 

IOTICS provides the infrastructure that supports the “FAIRification” process. In other words, you can use your IOTICSpace to make your data FAIR and secure.

A closer look 

Let’s take a closer look at what these data principles actually mean:


The first step in digital twins of asset interoperating across ecosystems is ensuring the digital twin and its (meta)data is findable by both authorised humans and computers.

A key factor in the FAIR process is that the (meta)data must have unique and persistent identifiers that provide a simple mechanism to disambiguate whether two pieces of data (or two assets) refer to the same information (or are the same thing).  At IOTICS, each twin has a globally unique and persistent identifier which provides the identity of the twin, its keys and permissions. 

The data should also be described with rich metadata meaning that there should be generous and extensive information about the characteristics, quality, context and condition of the data. The metadata should of course clearly and explicitly include the identifier of the data they describe. 

There’s little reason in having globally unique and persistent identifiers, or rich metadata, if no one knows where it exists or where to look for it. For data to be findable it’s crucial that data is registered or indexed in a searchable source so that researchers can discover it. 


Once the data has been found, the next step is that the user/computer needs to be able to access it. This may require authentication and authorisation.

Data is retrievable from their identifiers on the web without the need for specialised tools, assets (their data and metadata) are accessible, where appropriate authorisation exists,  because digital twins in IOTICS are accessible using standard protocols and technologies.


The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing.

Data needs to use a shared approach in order to be interoperable. A shared approach, using semantic web technologies, where users semantically model their assets underpins interoperability without the need for global universal common data models. 

In IOTICSpace semantic web technologies ensure each digital twin’s metadata is expressed as a triple subject/predicate/object; where the subject can be a link to a term part of an ontology. 

Assets interoperate with each other by means of their twins. A twin can describe and “understand” what any other accessible twin is about by virtue of its metadata and data being semantically modelled. 


This is the final step in the FAIRification process and the ultimate goal of FAIR. What this means is that data can be used in multiple different settings and used more than once. To achieve this, data and metadata should be well described so they can be replicated and combined in different settings. 

IOTICS encourages the producer to use “product thinking” when creating twins. Twins (and by definition the underlying assets) are reusable as their (meta)data can be repurposed. 



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