rfair 0.1.0

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").