dataverse (version 0.2.0)

create_dataset: Create or update a dataset

Description

Create or update dataset within a Dataverse

Usage

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"), ...)

Arguments

dataverse

A character string specifying a Dataverse name or an object of class “dataverse”.

body

A list describing the dataset.

key

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").

server

A character string specifying a Dataverse server. There are multiple Dataverse installations, but the defaults is to use the Harvard Dataverse. This can be modified atomically or globally using Sys.setenv("DATAVERSE_SERVER" = "dataverse.example.com").

...

Additional arguments passed to an HTTP request function, such as GET, POST, or DELETE.

dataset

An integer specifying a dataset identification number or an object of class “dataverse_dataset”. The identification number is the dataset's persistent identification number (not the integer specifying a specific version of the dataset, such as returned by dataset_versions).

Value

An object of class “dataverse_dataset”.

Details

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 publised (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).

See Also

get_dataset, delete_dataset, publish_dataset

Examples

# NOT RUN {
meta <- list()
ds <- create_dataset("mydataverse", body = meta)

meta2 <- list()
update_dataset(ds, body = meta2)

# cleanup
delete_dataset(ds)
# }