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Assess the FAIRness of the data and code shared in articles (rtransparent)

Source: R/assess_data_code.R
assess_data_code.Rd

Bridges rtransparent and rfair: takes the data/code identifiers rtransparent extracts from articles (its open_data_links and open_code_links columns) and scores each against the FAIR metrics. Data identifiers are scored with the FsF data metrics and code repositories with the FRSM software metrics.

Usage

assess_data_code(
  x,
  id_col = NULL,
  data_metric_version = "0.8",
  code_metric_version = "0.7_software",
  data_col = "open_data_links",
  code_col = "open_code_links",
  sep = " ; ",
  quiet = FALSE,
  workers = 1L,
  keep = FALSE,
  previous = NULL,
  ...
)

Arguments

x

One of: a data frame from rtransparent::rt_data_code_pmc() / rt_all_pmc() (with open_data_links / open_code_links columns); a named list with those elements; or a character vector of " ; "-joined data-link strings.

id_col

Optional name of a column in x identifying the source article (e.g. "pmid" or "doi"); used to label each result.

data_metric_version

Metric version for data identifiers (default "0.8").

code_metric_version

Metric version for code repositories (default "0.7_software").

data_col, code_col

Column/element names holding the joined links (defaults match rtransparent: "open_data_links", "open_code_links").

sep

Separator rtransparent uses to join identifiers (default " ; ").

quiet

If FALSE (default), print per-identifier progress.

workers, keep

See assess_fair_batch(). With keep = TRUE the "assessments" attribute holds the objects for data and code together.

previous

Optional result of an earlier assess_data_code() call, to resume an interrupted run (see assess_fair_batch()).

...

Passed to assess_fair().

Value

A data frame with one row per (article, kind, identifier): source (article id), kind ("data" or "code"), and the columns of assess_fair_batch(). Each unique identifier is assessed once.

See also

assess_fair_batch(), split_identifiers(), assess_fair()

Examples

# \donttest{
assess_data_code(list(open_data_links = "https://doi.org/10.5281/zenodo.8347772",
                      open_code_links = "https://github.com/pangaea-data-publisher/fuji"))
#> [1/1] assessing https://doi.org/10.5281/zenodo.8347772
#> [1/1] assessing https://github.com/pangaea-data-publisher/fuji
#>   source kind                                     identifier metric_version
#> 1   <NA> data         https://doi.org/10.5281/zenodo.8347772            0.8
#> 2   <NA> code https://github.com/pangaea-data-publisher/fuji   0.7_software
#>   scheme is_persistent resolved http_status
#> 1    doi          TRUE     TRUE         200
#> 2    url         FALSE     TRUE         200
#>                                     resolved_url fair_percent   F   A      I
#> 1             https://zenodo.org/records/8347772        88.46 100 100  66.67
#> 2 https://github.com/pangaea-data-publisher/fuji        91.11  95 100 100.00
#>       R maturity n_pass n_metrics error
#> 1 83.33      2.5     15        17  <NA>
#> 2 81.25      2.5     17        17  <NA>
# }