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Using the safedata system

There are three stages for data managers in using the safedata system, all of which use functionality provided by the safedata_validator package.

  1. Validation of datasets using the safedata_validate tool. It is perfectly possible for data providers themselves to install and configure safedata_validator and this may be useful if you have a lot of data coming from few sources. However, it is more usual for the data manager to receive datasets and then go through a few cycles of validation and checking before a dataset is ready.

  2. Publication of datasets using the safedata_zenodo tool. Once a dataset has been validated, then it is ready for publication to the project Zenodo community. This involves creating a new Zenodo record, uploading the data files themselves and then filling in the required Zenodo metadata.

  3. Uploading dataset metadata using the safedata_server tool. If you are maintaining a metadata server to support data discovery and use of the safedata R package, then the metadata for the published dataset needs to be uploaded to the server.

The pages linked above provide examples of using the safedata_validator package. Typically, data managers will use the command line interface using a Unix-like shell or Windows subsystem for Linux, but the pages also show how to use the programmatic API for safedata_validator from within Python.