---
title: "Beyond F-UJI: reuse, sensitivity, hygiene, and FAIR-TLC"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Beyond F-UJI: reuse, sensitivity, hygiene, and FAIR-TLC}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
library(rfair)
```

Automated FAIR tools have well-documented blind spots. In peer review of a
COVID-19 FAIR-assessment study, the reviewer (Melissa Haendel) noted that such
tools reward the *presence* of a license, an identifier, or a metadata field
without checking whether the data is actually reusable, legitimately restricted,
or properly identified. `rfair` adds checks for exactly these.

## A license can be present yet not open for reuse

Detecting that a license exists says nothing about whether you may reuse the
data. `license_reuse()` classifies the actual permissions, and maps each license
to the six-category taxonomy of the [(Re)usable Data
Project](https://reusabledata.org) (Carbon et al. 2019).

```{r}
license_reuse("https://creativecommons.org/licenses/by/4.0/")[c("category", "rdp_category", "facilitates_reuse")]
license_reuse("https://creativecommons.org/licenses/by-nc-nd/4.0/")[c("category", "rdp_category", "facilitates_reuse")]
```

Only *permissive* licenses facilitate reuse without negotiation; CC-BY-NC-ND is
present and standard, yet restrictive.

## Controlled-access and sensitive data is not a FAIR failure

Data behind a data-use agreement (e.g. human/clinical data) is legitimately
restricted; it should be judged on metadata richness, not open download.
`classify_access()` flags this, drawing on the (Re)usable Data Project
curations.

```{r}
classify_access(access_level = "closedAccess",
                urls = "https://www.ncbi.nlm.nih.gov/gap/?term=phs000424")[c("access", "controlled_access", "sensitive")]
```

## Identifier hygiene

Layered identifiers (an identifier minted on top of another) and non-persistent
identifiers reduce interoperability.

```{r}
identifier_hygiene("RRID:MGI:5577054")$issues
identifier_hygiene("https://doi.org/10.5281/zenodo.8347772")$hygiene_ok
```

## FAIR-TLC: Traceable, Licensed, Connected

The reviewer's own framework extends FAIR with three principles
([Haendel et al., FAIR+](https://doi.org/10.5281/zenodo.203295)): data should be
**Traceable** (provenance, attribution), **Licensed** (clearly and reusably),
and **Connected** (qualified links to related entities). `fair_tlc()` computes
these from an assessment.

```{r, eval = FALSE}
a <- assess_fair("https://doi.org/10.5281/zenodo.8347772")
fair_tlc(a)
#>   dimension                             indicator   met
#> 1 Traceable                         T1 Provenance  TRUE
#> 2 Traceable                        T2 Attribution  TRUE
#> 3  Licensed L1 Documented & minimally restrictive  TRUE
#> 4  Licensed           L2 Flowthrough transparency  TRUE
#> 5 Connected                      C1 Connectedness  TRUE
```

## The canonical FAIR principles

For reference, the authoritative principle definitions (from the FAIR-nanopubs
vocabulary used by go-fair.org):

```{r}
head(fair_principles(), 4)
```