What are the F.A.I.R principles?
The FAIR principles are a set of guidelines for making data Findable, Accessible, Interoperable, and Reusable. These principles were introduced to address the challenges of data sharing and reuse in scientific research, but they can also be applied to other domains.
These principles aim to promote openness, collaboration and the maximization of data’s potential value in scientific research and beyond.
The F.A.I.R. principles are a set of four principles that were introduced to address the challenges of data sharing and reuse in scientific research, but they can also be applied to other domains.
It helps strengthen the process when data are captured, recorded and reused.
Those who are using data every day – which include data scientists and data analysts, are looking for ways to boost the integrity and quality of the data capture process.
These four F.A.I.R. principles provide guidelines to data analysts to help support them to ensure that the data is obtained and recorded in an efficient and systematic fashion. Once these elements have been met, it makes it easier to access the data and re-use it.
These principles aim to promote openness, collaboration and the maximization of data’s potential value in scientific research and beyond.
What it means to be F.A.I.R.
Research data is often not used past its intended purpose. In fact, in many cases, scientific data is not shared or even re-usable.
This could be due to data protection or because the data is difficult to find. Imagine the potential of that data if it was used beyond its original goal. Think of what that could mean for medical breakthroughs in disease, or innovative alternative energy options. The benefits to society would be momentous.
Those dealing with data every day, including researchers, funders, and publishers, are looking to make scientific data more accessible and boost its value. Providing other researchers and scientists access to your data makes new discoveries easier and encourages transparency in research.
To get there, participants of the Lorentz Workshop “Jointly Designing a Data FAIRport” in 2014 came up with ‘The F.A.I.R. Principles for scientific data management and stewardship’ to guide researchers towards optimizing data sharing and ensuring data could be re-used by both humans and machines.
But what exactly does it mean to be F.A.I.R.? In this article, we’ll dig into what F.A.I.R. means and why it matters.
