Create a new Dataverse
create_dataverse(
dataverse,
key = Sys.getenv("DATAVERSE_KEY"),
server = Sys.getenv("DATAVERSE_SERVER"),
...
)A character string specifying a Dataverse name or an object of class “dataverse”. If missing, a top-level Dataverse is created.
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 list.
This function can create a new Dataverse. In the language of Dataverse, a user has a “root” Dataverse into which they can create further nested Dataverses and/or “datasets” that contain, for example, a set of files for a specific project. Creating a new Dataverse can therefore be a useful way to organize other related Dataverses or sets of related datasets.
For example, if one were involved in an ongoing project that generated monthly data. One may want to store each month's data and related files in a separate “dataset”, so that each has its own persistent identifier (e.g., DOI), but keep all of these datasets within a named Dataverse so that the project's files are kept separate the user's personal Dataverse records. The flexible nesting of Dataverses allows for a number of possible organizational approaches.
To manage Dataverses: delete_dataverse, publish_dataverse, dataverse_contents; to get datasets: get_dataset; to search for Dataverses, datasets, or files: dataverse_search
if (FALSE) { # \dontrun{
(dv <- create_dataverse("mydataverse"))
# cleanup
delete_dataverse("mydataverse")
} # }