A design framework and exemplar metrics for FAIRness | Scientific Data

ab1630's bookmarks 2018-06-27

Summary:

"The FAIR Principles1 (https://doi.org/10.25504/FAIRsharing.WWI10U) provide guidelines for the publication of digital resources such as datasets, code, workflows, and research objects, in a manner that makes them Findable, Accessible, Interoperable, and Reusable (FAIR). The Principles have rapidly been adopted by publishers, funders, and pan-disciplinary infrastructure programmes and societies. The Principles are aspirational, in that they do not strictly define how to achieve a state of "FAIRness", but rather they describe a continuum of features, attributes, and behaviors that will move a digital resource closer to that goal. This ambiguity has led to a wide range of interpretations of FAIRness, with some resources even claiming to already "be FAIR"! The increasing number of such statements, the emergence of subjective and self-assessments of FAIRness2,3, and the need of data and service providers, journals, funding agencies, and regulatory bodies to qualitatively or quantitatively evaluate such claims, led us to self-assemble and establish a FAIR Metrics group (http://fairmetrics.org) to pursue the goal of defining ways to measure FAIRness...."

Link:

https://www.nature.com/articles/sdata2018118

From feeds:

Open Access Tracking Project (OATP) ยป ab1630's bookmarks

Tags:

oa.new oa.fair oa.data oa.standards oa.metrics oa.reproducibility oa.open_science

Date tagged:

06/27/2018, 15:03

Date published:

06/27/2018, 11:03