Rationale
There is a pressing need to provide concrete demonstrations of the benefits of linked data in order to help motivate the transition of library catalogs from MARC. Within LD4P2, work to enhance the discovery of library resources is the focus of WP4: Discovery. The partners have committed to working with the Blacklight framework to demonstrate enhanced discovery features such as:
- knowledge panel in search results to present contextual information powered by linked data;
- browsing based on authority files and links to related entities in external data;
- semantic search, which could include laying out alternative terms in a “no results” page, suggesting semantically related terms in a type-ahead, or providing richer, geo-based browse by leveraging URIs for places; and
- microdata on item pages to enable machine crawling.
In all of these areas there is opportunity for community input on and discussion of the best approaches and the desired outcomes. The LD4 Discovery Affinity Group will provide a forum for these discussions, with the following goals:
- identify exemplar systems/features the demonstrate the benefits of linked data and could be applied to library resources
- identify opportunities for enhanced discovery of library resources using linked data that can be implemented in the short to medium term
- document connections between cataloging practices and discovery outcomes
- document effective assessment approaches
- provide advice to LD4P2 partners and cohort members for WP4: Discovery
Approach
- Co-chaired by Tom Cramer & Simeon Warner (at least to start)
- Monthly calls
- Announce on
ld4-discuss - Public notes posted on this wiki
- Topics seeded in advance, with a few key speakers drawn from community, then discussion
- Announce on
- Dedicated, open Slack channel in LD4 –
#discovery - Dedicated, open Google Group –
ld4-discovery - Share brief updates on all hands calls
- Consider face-to-face sessions at the LD4 conference each Spring
Ideas for call topics
(Each call might be themed around 1 or more of these questions)
- examples of knowledge panels. What works, works well, where is data coming from?
- can you tell if schema.org <http://schema.org> works / is worth the effort?
- how Wikidata can make Library discovery better
- cohort Discovery projects: Yale, UC Davis, Harvard, etc.
- what examples of browse interfaces to you have / like?
- semantic search? advanced discovery?
- how do you assess impact of exposing your metadata as LOD?
- tips and tricks for better metadata production
- "if I do x in my catalog record, I get y result"
- other topics as they arise...
