Changes in version 0.1.0 (2026-07-01)                  

First release. rfair is a native R implementation of the F-UJI /
FAIRsFAIR research data object assessment metrics and the FRSM (FAIR for
Research Software) metrics. It performs the entire assessment in R, with
no external server.

Assessment

  - assess_fair() resolves a DOI, persistent identifier, URL, or code
    repository, harvests its metadata, and scores it against the FAIR
    metrics, returning a fair_assessment object.
  - Multiple metric sets, listed by rfair_metric_versions(): the current
    F-UJI data metrics (v0.8) by default, several legacy and
    domain-specific versions (0.2-0.8, plus social-science and
    environmental variants), and the FRSM research-software metrics
    (0.7).
  - Metadata harvesting from registries (DataCite, Crossref, GitHub),
    landing-page embedded metadata (schema.org JSON-LD, Dublin Core,
    OpenGraph, Highwire), signposting and typed links,
    content-negotiated XML (DataCite XML, MODS, EML, ISO 19139) and RDF
    / JSON-LD, and optional user-supplied metadata-service endpoints
    (OAI-PMH, OGC CSW, SPARQL, DCAT, schema.org, RO-Crate, CKAN).
  - Software FAIR: pass a GitHub repository with metric_version =
    "0.7_software" to score it against the FRSM metrics from its
    repository signals (license, README, citation/codemeta, tests, CI,
    dependencies, coverage, releases, contributors). The FRSM metrics
    operationalize the FAIR Principles for Research Software (FAIR4RS;
    Chue Hong et al. 2022, doi:10.15497/RDA00068).
  - id_parse() recognizes DOI, Handle, ARK, URN, UUID, identifiers.org /
    w3id, and compact prefix:accession identifiers.

Working with the result

  - The fair_assessment object has print(), summary(), as.data.frame(),
    and plot() methods. plot() draws a category scorecard, a per-metric
    breakdown, or a concentric FAIR "sunburst".
  - as_fuji_json() exports the assessment in the F-UJI FAIRResults JSON
    schema; as_rdf() exports W3C DQV quality measurements plus a
    schema.org Rating (JSON-LD or, with rdflib, Turtle).
  - A bundled example assessment, fair_example, is provided for offline
    use.

Beyond F-UJI

  - license_reuse() judges whether a license actually permits reuse,
    using the (Re)usable Data Project taxonomy; reusabledata_rating()
    looks up curated repository ratings.
  - classify_access() flags controlled-access and sensitive data (which
    are not FAIR failures).
  - identifier_hygiene() checks identifiers for layered or
    non-persistent forms.
  - fair_tlc() reports the FAIR-TLC (Traceable, Licensed, Connected)
    indicators.
  - fair_principles() and principle_definition() provide the canonical
    FAIR principle definitions; fair4rs_principles() provides the
    FAIR4RS principles for research software, and principle_definition()
    resolves FRSM software metrics to their FAIR4RS statement.

Batch assessment and rtransparent

  - assess_fair_batch() scores a vector of identifiers into one tidy row
    each.
  - assess_data_code() ingests the data and code identifiers that the
    rtransparent package extracts from articles (its open_data_links and
    open_code_links) and scores each (FsF for data, FRSM for code).
  - split_identifiers() parses the " ; "-joined identifier strings.

Interfaces

  - launch_rfair() opens a bslib Shiny app for interactive assessment.
  - A no-install browser version is published at
    https://choxos.github.io/rfair/app/.
  - A Plumber API scaffold and an OpenAPI contract are installed under
    system.file("plumber", package = "rfair") and system.file("openapi",
    package = "rfair").