Most explanations of the FAIR data principles are written by academic data stewards for academic data stewards, and the examples involve depositing genomics datasets in public repositories. A QC ...

This work provides a guide that enables researchers to create and evaluate whether data sets adhere to FAIR principles. This will allow both humans and machines to use (and re-use) data sets, ...

Every clinical lab generates data, but not all of it remains usable for colleagues, regulators, or even the lab itself months later. In this era of digitized health systems, increased regulatory ...

In research, healthcare and biotechnology, there is a growing need to improve support for the reuse of data. But data sets are often incomplete, lack proper documentation or lack accessibility, making ...

Visualization of Bragg diffraction peaks in an undeformed bi-crystal gold sample. The height denotes photon counts. This data was produced at the Advanced Photon Source and processed at the ThetaGPU ...

FAIR data principles aim to automate data management, paving the way to link data sources, AI, extreme scale, and edge computing with modern scientific data infrastructure to automate and accelerate ...