FAIR for AI: An interdisciplinary and international community building perspective
A foundational set of findable, accessible, interoperable, and reusable (FAIR) principles
were proposed in 2016 as prerequisites for proper data management and stewardship, with …
were proposed in 2016 as prerequisites for proper data management and stewardship, with …
A design framework and exemplar metrics for FAIRness
The FAIR Principles 1 (https://doi. org/10.25504/FAIRsharing. WWI10U) provide guidelines
for the publication of digital resources such as datasets, code, workflows, and research …
for the publication of digital resources such as datasets, code, workflows, and research …
FAIR adoption, assessment and challenges at UniProt
UniProt continues to support the ongoing process of making scientific data FAIR. Here we
contribute to this process with a FAIRness assessment of our UniProtKB dataset followed by …
contribute to this process with a FAIRness assessment of our UniProtKB dataset followed by …
Towards FAIR principles for research software
AL Lamprecht, L Garcia, M Kuzak, C Martinez… - Data …, 2020 - content.iospress.com
The FAIR Guiding Principles, published in 2016, aim to improve the findability, accessibility,
interoperability and reusability of digital research objects for both humans and machines …
interoperability and reusability of digital research objects for both humans and machines …
Making FAIR easy with FAIR tools: From creolization to convergence
M Thompson, K Burger, R Kaliyaperumal, M Roos… - Data …, 2020 - direct.mit.edu
Since their publication in 2016 we have seen a rapid adoption of the FAIR principles in
many scientific disciplines where the inherent value of research data and, therefore, the …
many scientific disciplines where the inherent value of research data and, therefore, the …
An automated solution for measuring the progress toward FAIR research data
A Devaraju, R Huber - Patterns, 2021 - cell.com
With a rising number of scientific datasets published and the need to test their Findable,
Accessible, Interoperable, and Reusable (FAIR) compliance repeatedly, data stakeholders …
Accessible, Interoperable, and Reusable (FAIR) compliance repeatedly, data stakeholders …
The FAIR principles: First generation implementation choices and challenges
B Mons, E Schultes, F Liu, A Jacobsen - Data Intelligence, 2020 - direct.mit.edu
“FAIR enough”?... A question asked on a daily basis in the rapidly evolving field of open
science and the underpinning data stewardship profession. After the publication of the FAIR …
science and the underpinning data stewardship profession. After the publication of the FAIR …
FAIRshake: toolkit to evaluate the findability, accessibility, interoperability, and reusability of research digital resources
DJB Clarke, L Wang, A Jones, ML Wojciechowicz… - BioRxiv, 2019 - biorxiv.org
As more datasets, tools, workflows, APIs, and other digital resources are produced by the
research community, it is becoming increasingly difficult to harmonize and organize these …
research community, it is becoming increasingly difficult to harmonize and organize these …
[PDF][PDF] The FAIR Guiding Principles for scientific data management and stewardship
M Axton, A Baak, N Blomberg, JW Boiten… - Scientific data, 2016 - core.ac.uk
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data.
A diverse set of stakeholders—representing academia, industry, funding agencies, and …
A diverse set of stakeholders—representing academia, industry, funding agencies, and …
Considerations for the conduction and interpretation of FAIRness evaluations
R de Miranda Azevedo, M Dumontier - Data Intelligence, 2020 - direct.mit.edu
The FAIR principles were received with broad acceptance in several scientific communities.
However, there is still some degree of uncertainty on how they should be implemented …
However, there is still some degree of uncertainty on how they should be implemented …