Metadata Export

Automatic Exports

Publishing a dataset automatically starts a metadata export job, that will run in the background, asynchronously. Once completed, it will make the dataset metadata exported and cached in all the supported formats:

  • Dublin Core
  • Data Documentation Initiative (DDI)
  • native JSON (Dataverse-specific)

A scheduled timer job that runs nightly will attempt to export any published datasets that for whatever reason haven’t been exported yet. This timer is activated automatically on the deployment, or restart, of the application. So, again, no need to start or configure it manually. (See the “Application Timers” section of this guide for more information)

Batch exports through the API

In addition to the automated exports, a Dataverse admin can start a batch job through the API. The following 2 API calls are provided:



The former will attempt to export all the published, local (non-harvested) datasets that haven’t been exported yet. The latter will force a re-export of every published, local dataset, regardless of whether it has already been exported or not.

Note, that creating, modifying, or re-exporting an OAI set will also attempt to export all the unexported datasets found in the set.

Export Failures

An export batch job, whether started via the API, or by the application timer, will leave a detailed log in your configured logs directory. This is the same location where your main Glassfish server.log is found. The name of the log file is export_[timestamp].log - for example, export_2016-08-23T03-35-23.log. The log will contain the numbers of datasets processed successfully and those for which metadata export failed, with some information on the failures detected. Please attach this log file if you need to contact Dataverse support about metadata export problems.