Create or update dataset within a Dataverse
create_dataset(
dataverse,
body,
key = Sys.getenv("DATAVERSE_KEY"),
server = Sys.getenv("DATAVERSE_SERVER"),
...
)
update_dataset(
dataset,
body,
key = Sys.getenv("DATAVERSE_KEY"),
server = Sys.getenv("DATAVERSE_SERVER"),
...
)A character string specifying a Dataverse name or an object of class “dataverse”.
A list describing the dataset.
A character string specifying a Dataverse server API key. If one
is not specified, functions calling authenticated API endpoints will fail.
Keys can be specified atomically or globally using
Sys.setenv("DATAVERSE_KEY" = "examplekey").
A character string specifying a Dataverse server.
Multiple Dataverse installations exist, with "dataverse.harvard.edu" being the
most major. The server can be defined each time within a function, or it can
be set as a default via an environment variable. To set a default, run
Sys.setenv("DATAVERSE_SERVER" = "dataverse.harvard.edu")
or add DATAVERSE_SERVER = "dataverse.harvard.edu" in one's .Renviron
file (usethis::edit_r_environ()), with the appropriate domain as its value.
Additional arguments passed to an HTTP request function,
such as GET, POST, or
DELETE. See use_cache for details
on how the R dataverse package uses disk and session caches to
improve network performance.
A character specifying a persistent identification ID for a dataset,
for example "10.70122/FK2/HXJVJU". Alternatively, an object of class
“dataverse_dataset” obtained by dataverse_contents().
An object of class “dataverse_dataset”.
create_dataset creates a Dataverse dataset. In Dataverse, a “dataset” is the lowest-level structure in which to organize files. For example, a Dataverse dataset might contain the files used to reproduce a published article, including data, analysis code, and related materials. Datasets can be organized into “Dataverse” objects, which can be further nested within other Dataverses. For someone creating an archive, this would be the first step to producing said archive (after creating a Dataverse, if one does not already exist). Once files and metadata have been added, the dataset can be published (i.e., made public) using publish_dataset.
update_dataset updates a Dataverse dataset that has already been created using create_dataset. This creates a draft version of the dataset or modifies the current draft if one is already in-progress. It does not assign a new version number to the dataset nor does it make it publicly visible (which can be done with publish_dataset).
if (FALSE) { # \dontrun{
meta <- list()
ds <- create_dataset("mydataverse", body = meta)
meta2 <- list()
update_dataset(ds, body = meta2)
# cleanup
delete_dataset(ds)
} # }