frictionless workflows with deposits
As described in the main README, the deposits package is designed to work with rOpenSci’s
frictionless package for documentation of datasets. The
frictionless package is an R implementation of the general “frictionless” workflow. All deposits metadata, both for a deposit in general as described in the accompanying metadata vignette, and for the internal structure of datasets, are stored in a single “frictionless” metadata file called “datapackage.json”.
This vignette describes how to generate those files, and how to use them to manage deposits metadata.
Generating “datapackage.json” files
The deposits package uses the
frictionless R package to automatically generate frictionless metadata files named “datapackage.json” for any tabular input data. These files can only be generated for one or more input data sets, and so can not be generated for deposits metadata without accompanying data files or resources.
The following code is repeated from the main vignette, and generates a local data file with some tabular data in an empty directory.
dir.create (file.path (tempdir (), "data")) path <- file.path (tempdir (), "data", "beaver1.csv") write.csv (datasets::beaver1, path, row.names = FALSE)
We then need to construct a deposits client, and specify metadata, in this case those describing the
beaver1 dataset. The format of these metadata is explained at length in the metadata vignette.
metadata <- list ( creator = list (list (name = "P. S. Reynolds")), created = "1994-01-01T00:00:00", title = "Time-series analyses of beaver body temperatures", description = "Original source of 'beaver' dataset." ) cli <- depositsClient$new (service = "zenodo", sandbox = TRUE, metadata = metadata)
Generation by uploading files
The main vignette demonstrates how to use these metadata to initiate a new deposit on the Zenodo sandbox service, and then to upload the local data. Calling the
deposit_upload_file() method automatically generates a “datapackage.json” file (if one does not already exist), adds deposits metadata, and also uploads that file to the deposits service.
cli$deposit_new () #> ID of new deposit : 1162420 cli$deposit_upload_file (path = path) #> frictionless metadata file has been generated as '/tmp/RtmpvRre5Z/data/datapackage.json'
The client then lists two files that were uploaded, and the local directory also now has a “datapackage.json” file:
cli$hostdata$files$filename #>  "beaver1.csv" "datapackage.json" list.files (file.path (tempdir (), "data")) #>  "beaver1.csv" "datapackage.json"
The deposits package inserts an additional “metadata” field into the frictionless metadata file, containing the deposits metadata defined above. This method of generating frictionless metadata files requires data to first be uploaded to a service, and will automatically upload the frictionless metadata file. Any subsequent editing then requires repeated calls to the
deposit_upload_file() method to update the contents of this file.
A frictionless metadata file can also first be generated locally, to allow editing prior to any uploading. This is achieved with the
deposit_add_resource() method. As mentioned, the frictionless workflow requires a data “resource” to exist. The resource in the above example is the locally-stored “beaver.csv” file. Presuming this file to exist, we can again initiate a deposit, and then to call
deposit_add_resource(), instead of
cli <- depositsClient$new (service = "zenodo", sandbox = TRUE, metadata = metadata) cli$deposit_add_resource (path = path)
That call will generate a local frictionless metadata file (if one does not already exist), and fill it with the deposits metadata, without initiating a new deposit or uploading any files. Whether generated and immediately uploading through calling
deposit_upload_file(), or locally generated only through calling
deposit_add_resource(), the frictionless data file can then be edited and updated as described in the following sub-section.
Note that calling either of these methods connects the client to the local directory containing the “datapackage.json” file and other data files. Printing the client then produces additional information including a
local_path identifying the directory, along with counts of both local and remote “resources” or files.
Reading and editing “datapackage.json” files
The “datapackage.json” file can be read with the
frictionless::read_package() function, returning a named list of metadata entries:
library (frictionless) path <- file.path (tempdir (), "data", "datapackage.json") metadata <- read_package (path) names (metadata) #>  "profile" "metadata" "resources" "directory"
The “profile”, “resources”, and “directory” items are all generated by
frictionless, while the “metadata” items holds the deposits metadata entered above:
metadata$metadata #> $created #>  "1994-01-01T00:00:00" #> #> $creator #> $creator[] #> $creator[]$name #>  "P. S. Reynolds" #> #> $description #>  "Original source of 'beaver' dataset." #> #> $title #>  "Time-series analyses of beaver body temperatures"
frictionless aspects of the metadata are by default automatically generated by that package, and generally benefit from the kind of editing and enhancing described in the main
frictionless vignette, including such things as adding descriptions of variables. The deposits-specific “metadata” component can also readily be extended and edited as desired.
The data in these files can be edited in two primary ways, through either:
- Editing the individual list items in R, and saving the result via
- Directly editing the “datapackage.json” with a text editor.
We recommend the second method, as it enables the simplest overview over the entire metadata structure for a given deposit. Once a frictionless “datapackage.json” file has been generated for a deposit, the recommended deposits workflow is for all editing and updating of metadata to be done by directly editing that file, as explained in the metadata vignette.
Updating “datapackage.json” on deposits service
Any changes to a local “datapackage.json” file can be imported into a deposits client with the
deposit_update() method, which will also update the remote version of the “datapackage.json” file held on the deposits service. Because the initial
deposit_add_resource() methods both connected the client to the local directory containing the deposit data, the update method can be called directly without any parameters. Specific paths can nevertheless be passed to the
deposit_update() method, to update only specified files while ignoring changes in any other files. For example, the
path argument can specify the path to the single “datapackage.json” file, in which case only that file will be uploaded, regardless of any local modifications to other files.
cli$deposit_update () #> Local file at [/tmp/Rtmp5QfAEc/data/beaver1.csv] is identical on host and will not be uploaded. #> Local file at [/tmp/Rtmp5QfAEc/data/datapackage.json] has changed and will now be uploaded.
Calling that method will update both the “metadata” and “hostdata” elements of the deposits client to reflect any changes made to the “datapackage.json” file, and will also update the remote version of that file, as indicated in the messages produced by calling that method.