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rfair assesses how well a research data object satisfies
the FAIR principles (Findable, Accessible, Interoperable, Reusable),
entirely in R. It is a native port of the F-UJI metrics,
so it needs no external assessment server.
Pass any DOI, persistent identifier, or URL to
assess_fair(). It resolves the identifier, harvests
metadata, and scores it against the FAIRsFAIR metrics.
The returned fair_assessment object prints an F/A/I/R
summary. The numbers come from up to 17 metrics; each is one row of:
summary(a) gives the per-principle score table, and the
maturity column reports a 0–3 CMMI level (incomplete →
advanced).
Automated FAIR scores have well-known blind spots. rfair
surfaces three:
# A license being *present* does not mean the data is open for reuse.
a$reuse # per-license: open / restrictive, commercial, derivatives
# Restricted access can be legitimate (e.g. sensitive human data) and should not
# be read as "not FAIR".
a$access # access level, controlled_access, sensitive
# Identifiers should follow best practices.
a$identifier_hygiene # layered / non-persistent identifier warningsYou can call these directly too:
A no-install browser version is at https://choxos.github.io/rfair/app/; because browsers cannot fetch landing pages cross-origin, it scores from registry metadata (DataCite/Crossref) only, so some metrics are lower than the R engine.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.