scholid

scholid provides lightweight, dependency-free utilities for working with scholarly identifiers in R. The package is designed as a small, well-tested foundation that can be safely reused by other packages and data workflows.

Installation

Install the released version from CRAN:

install.packages("scholid")

Scope

The package focuses on common identifier systems used in scholarly communication:

• DOI
• ORCID iD
• ISBN
• ISSN
• arXiv
• PubMed (PMID)
• PubMed Central (PMCID)

Interface

User-available functions:

Function	Purpose
scholid_types()	List supported scholarly identifier types
is_scholid(x, type)	Test whether values conform to a given identifier type
normalize_scholid(x, type)	Normalize identifiers to canonical form
extract_scholid(text, type)	Extract identifiers of a given type from free text
classify_scholid(x)	Guess the identifier type of each input value
detect_scholid_type(x)	Detect identifier types from canonical or wrapped input values

Examples

# list supported scholarly identifier types
scholid::scholid_types()

## [1] "arxiv" "doi"   "isbn"  "issn"  "orcid" "pmcid" "pmid"

# test whether values match a given identifier type
scholid::is_scholid(
  x    = "10.1000/182",
  type = "doi"
)

## [1] TRUE

# normalize identifiers to canonical form
scholid::normalize_scholid(
  x    = "https://doi.org/10.1000/182",
  type = "doi"
)

## [1] "10.1000/182"

# extract identifiers of a given type from free text
scholid::extract_scholid(
  text = "See https://doi.org/10.1000/182 for details.",
  type = "doi"
)

## [[1]]
## [1] "10.1000/182"

# classify the identifier type of each input value
scholid::classify_scholid(
  x = c(
    "10.1000/182",
    "0000-0002-1825-0097",
    "not an id"
  )
)

## [1] "doi"   "orcid" NA

# detect identifier types from canonical or wrapped input values
scholid::detect_scholid_type(
  x = c(
    "https://doi.org/10.1000/182",
    "ORCID: 0000-0002-1825-0097",
    "arXiv:2101.00001",
    "not an id"
  )
)

## [1] "doi"   NA      "arxiv" NA

For more detailed usage patterns, including extraction from text and classification of mixed identifier columns, see the Get started vignette.

License

MIT