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The fifth group of use cases explore including usage data to supplement library discovery interfaces and to inform collection review and additions. Here the team first explored a very granular model for capturing usage information from circulation-related events and other direct user interactions with library resources. On further investigation, however, this data proved not only to be difficult to come by but fraught with concerns about privacy, even when stripped of any directly identifying information. Later discussions have focused on the compilation and use of a simple 'stack score as a measure ' usage metric on a percentage scale potentially more comparable across institutions despite differences in size, discipline, population makeup, and other factors.
- David Weinberger: "A Good, Dumb Way to Learn from Libraries" from the Chronicle of Higher Education, October 7, 2014. This provides motivation and explanation for a simple usage metric that protects user privacy.
Expressing bibliographic metadata to support discovery
The LD4L use cases largely target specific ways to supplement traditional library catalog metadata, whether through linkages to external identities and resources, connecting catalog records with other digital collections, adding usage metrics, or annotations. Some go on to suggest new functionality by leveraging this new "library graph" in services that go beyond direct, text-based matching of search terms to suggest deeper connections and even loop back from externally linked entities to additional local resources or related resources in other libraries.
In parallel with enriching query results for users through additional linking, the LD4L project is also looking to better align bibliographic metadata with facets such as genre, format, uniform title, subject, and online availability to meet user expectations. Where indexing MARC metadata for search now typically requires complex case statements reflecting variations in local cataloging practice by discipline or over time, we see conversion to RDF as an opportunity to use ontologies to capture important user-facing facet values explicitly, thereby reducing reliance on 'black box' processing and increasing the interoperability of metadata and re-usability of tools across libraries despite historical differences in local cataloging practice.