Build the FAIR Implementation Profile
In an effort to accelerate broad community convergence on FAIR implementation options, the GO FAIR community has launched the development of machine-actionable FAIR Implementation Profiles (FIP). The FIP is a collection of FAIR implementation choices made by a community of practice for each of the FAIR Principles. Community specific FAIR Implementation Profiles are themselves captured as FAIR datasets and are made openly available to other communities for reuse.
The FAIR Implementation Profiles representing the implementation strategies of various communities can be used as the basis to optimize the reuse of existing FAIR-enabling resources and interoperation within and between domains. Ready-made and well-tested FAIR Implementation Profiles created by trusted communities can find widespread reuse among other communities, and vastly accelerate convergence onto well-informed FAIR implementations.
The FAIR Convergence Matrix is an online platform that systematically guides self-identified communities in the decision process leading to optimal FAIR implementations and practices. The role of FIPs in catalyzing convergence, especially between domains, have been highlighted during the GO FAIR/ CODATA Convergence Symposium, November 27 to December 4, 2020 during the session “Report on FIPs Presymposium Workshops” (November 30th, 16h00-18h00 CET).
What is your FIP?
Magagna, B, et al. 2020. Reusable FAIR Implementation Profiles as Accelerators of FAIR Convergence.
OSF Preprints: https://doi.org/10.31219/osf.io/2p85g
FAIR Implementation Profiles for three communities (purple nodes, center) listing resources enabling the F (teal), A (dark blue), I (brown) and R (gray) principles.
Figure courtesy of Barbra Magagna, Umweltbundesamt GmbH and
Kristina Hettne, CDS University Library Leiden
Three-point FAIRification icons
The official icons for the Three-Point FAIRification Framework (Metadata for Machines Workshops, FAIR Implementation Profile and FAIR Data Point) have been registered at Zenodo under the Creative Commons Attribution Share Alike 4.0 International license.