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, will be highlighted during the upcoming GO FAIR/ CODATA Convergence Symposium, November 30 to December 4, 2020.
FIP Working group
FIP and Matrix development has been underway since November 2018. A large collection of early-version FIPs covering a broad spectrum of research domains has now been assembled and analyzed. FIP development continues to be actively pursued within the working group.
Names of the working group members will be added to the website shortly. Should you like to participate in the M4M working group please get in touch with us via firstname.lastname@example.org.
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