Metadata is a collection of descriptors used to describe a single quantity of information (data about data). It enables you to attach descriptive tags to your learning objects and assets to provide a searchable context for the content you publish. Metadata can make the learning objects easier to find.
You can add metadata prior to publishing an object to the LOR. After attaching metadata to a learning object or an asset in the LOR, you can edit it in the LOR.
While the function of metadata is very powerful, the processes involved in creating and managing it are fairly simple to understand and implement once you familiarize yourself with them.
Metadata harvesting is the process of retrieving metadata information from other repositories and storing it locally.
Learning Repository supports metadata harvesting, acting as both harvester and providing metadata for external repositories. The harvesting feature uses the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) standards to handle requests for metadata. These standards are available at www.openarchives.org.
Harvesting allows you to search external repositories from within the Learning Repository interface, or allows external services to retrieve metadata from Learning Repository for searching within an external application.
For complex learning objects Learning Repository provides the harvester with course-level metadata.
Allowing others to harvest metadata from your LORs gives the other institution a link to the object as part of the metadata. The LOR remains in the Desire2Learn environment. External sites cannot access the files of the object, but they can click on the link to the object to view it if they authenticate with a user ID and password.
Note Metadata harvesting does not harvest hidden objects.
To use metadata harvesting, contact your Desire2Learn Account Manager for information on best practices and how to have the service installed on your instance.