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Retrieve scholarly metadata

Source: R/id_metadata.R
id_metadata.Rd

Retrieve structured metadata for scholarly identifiers from external registries.

Usage

id_metadata(
  x,
  type = c("auto", scholidonline_types()),
  provider = c("auto", .scholidonline_providers()),
  fields = NULL,
  ...,
  quiet = FALSE
)

Arguments

x

A character vector of identifiers.

type

A single identifier type string, or "auto" to infer the type for each element of x. See scholidonline_types() for supported values.

provider

A single provider string specifying which online service to use. Use "auto" to use the default provider for the resolved identifier type. In most cases, "auto" is appropriate.

fields

An optional character vector naming the columns to return. If NULL, all default columns are returned. Unknown field names are ignored.

...

Reserved for future provider-specific arguments.

quiet

A single logical value; if TRUE, suppress provider warnings and messages where possible.

Value

A data.frame with one row per input identifier. By default, the returned columns are input, type, provider, title, year, container, doi, pmid, pmcid, and url. Inputs that cannot be identified, normalized, or resolved are returned as rows with missing metadata fields.

Details

id_metadata() is vectorized over x and returns a data.frame with one row per input identifier.

The function returns a consistent cross-provider subset of core bibliographic metadata, such as title, publication year, container title, linked DOI, PMID, PMCID, and a canonical URL when available.

Examples

# \donttest{
  out <- id_metadata("10.1038/nature12373", type = "doi")
  knitr::kable(out)
#> 
#> 
#> |input               |type |provider |title                                        | year|container |doi                 |pmid |pmcid |url                                 |
#> |:-------------------|:----|:--------|:--------------------------------------------|----:|:---------|:-------------------|:----|:-----|:-----------------------------------|
#> |10.1038/nature12373 |doi  |crossref |Nanometre-scale thermometry in a living cell | 2013|Nature    |10.1038/nature12373 |NA   |NA    |https://doi.org/10.1038/nature12373 |
  out <- id_metadata(c("31452104", "PMC6821181"))
  knitr::kable(out)
#> 
#> 
#> |input      |type  |provider |title                                                    | year|container        |doi |pmid     |pmcid      |url                                                   |
#> |:----------|:-----|:--------|:--------------------------------------------------------|----:|:----------------|:---|:--------|:----------|:-----------------------------------------------------|
#> |31452104   |pmid  |ncbi     |Molegro Virtual Docker for Docking.                      | 2019|Methods Mol Biol |NA  |31452104 |NA         |https://pubmed.ncbi.nlm.nih.gov/31452104/             |
#> |PMC6821181 |pmcid |ncbi     |Figure and caption extraction from biomedical documents. | 2019|Bioinformatics   |NA  |NA       |PMC6821181 |https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6821181/ |
  out <- id_metadata(
    "10.1038/nature12373",
     fields = c("title", "year", "doi")
     )
  knitr::kable(out)
#> 
#> 
#> |title                                        | year|doi                 |
#> |:--------------------------------------------|----:|:-------------------|
#> |Nanometre-scale thermometry in a living cell | 2013|10.1038/nature12373 |
# }