Project Status: Active – The project has reached a stable, usable state and is being actively developed. cran checks R-CMD-check codecov.io rstudio mirror downloads cran version DOI

rdatacite provides programmatic accesses to DataCite (https://datacite.org/) metadata

rdatacite docs: https://docs.ropensci.org/rdatacite

Package API:

  • dc_providers
  • dc_reports
  • dc_check
  • dc_events
  • dc_dois
  • dc_clients
  • dc_client_prefixes
  • dc_provider_prefixes
  • dc_status
  • dc_prefixes
  • dc_activities

Installation

Stable CRAN version

install.packages("rdatacite")

Development version from github

pak::pkg_install("ropensci/rdatacite")

Result objects

Outputs from nearly all rdatacite functions will be of class dc, an S3 class that’s simply a named list of results. You can easily remove the class via unclass(). The print.dc method prints the data.frame for the data, included, and reports slots if they exist, but hides the meta named list. You can get to the metadata by indexing to it like $meta.

Searching

You may want to start with dc_dois().

dc_dois(query = "climate change")
#> datacite: dois
#> found: 85075, pages: 400, page: 1
#> slots: data, meta, links
#> $data
#> # A tibble: 25 x 4
#>    id    type  attributes$doi $identifiers $creators $titles $publisher
#>    <chr> <chr> <chr>          <list>       <list>    <list>  <chr>     
#>  1 10.1… dois  10.15786/20.5… <list [0]>   <df[,6] … <df[,1… Mountain …
#>  2 10.2… dois  10.25675/1021… <list [0]>   <df[,3] … <df[,2… Mountain …
#>  3 10.2… dois  10.25675/1021… <list [0]>   <df[,3] … <df[,2… Mountain …
#>  4 10.2… dois  10.25675/1021… <list [0]>   <df[,3] … <df[,2… Mountain …
#>  5 10.2… dois  10.25675/1021… <list [0]>   <df[,3] … <df[,2… Mountain …
#>  6 10.2… dois  10.25676/1112… <list [0]>   <df[,6] … <df[,1… Mountain …
#>  7 10.2… dois  10.25676/1112… <list [0]>   <df[,6] … <df[,1… Mountain …
#>  8 10.2… dois  10.25675/1021… <list [0]>   <df[,6] … <df[,2… Mountain …
#>  9 10.2… dois  10.25675/1021… <list [0]>   <df[,6] … <df[,1… Mountain …
#> 10 10.2… dois  10.25675/1021… <list [0]>   <df[,6] … <df[,1… Mountain …
#> # … with 15 more rows, and 42 more variables: $container <df[,0]>,
#> #   $publicationYear <int>, $subjects <list>, $contributors <list>,
#> #   $dates <list>, $language <chr>, $types$ris <chr>, $$bibtex <chr>,
#> #   $$citeproc <chr>, $$schemaOrg <chr>, $$resourceType <chr>,
#> #   $$resourceTypeGeneral <chr>, $relatedIdentifiers <list>, $sizes <list>,
#> #   $formats <list>, $version <lgl>, $rightsList <list>, $descriptions <list>,
#> #   $geoLocations <list>, $fundingReferences <list>, $url <chr>,
#> #   $contentUrl <lgl>, $metadataVersion <int>, $schemaVersion <chr>,
#> #   $source <chr>, $isActive <lgl>, $state <chr>, $reason <lgl>,
#> #   $viewCount <int>, $downloadCount <int>, $referenceCount <int>,
#> #   $citationCount <int>, $partCount <int>, $partOfCount <int>,
#> #   $versionCount <int>, $versionOfCount <int>, $created <chr>,
#> #   $registered <chr>, $published <lgl>, $updated <chr>,
#> #   relationships$client$data$id <chr>, $$$type <chr>
#> 
#> $included
#> NULL

The query parameter supports Elasticearch query string queries. Some examples:

# search within a field
dc_dois(query = "publicationYear:2016")
# fuzzy search (via *) on a nested field
dc_dois(query = "creators.familyName:mil*")

Meta