LD4 Discovery Affinity Group Charge

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 LD4P3, work to enhance the discovery of library resources is the focus of WP3: Discovery. Within LD4P2, similar work was the focus of WP4: Discovery. The partners had 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 LD4P3 partners for WP3: Discovery
- (previously provided advice to LD4P2 partners and cohort members for WP4: Discovery)

Approach

Co-chaired by Astrid Usong & Huda Khan
- Jessie Keck: co-chair from 2019 - 3/2021
- originally chartered and chaired by Tom Cramer and Simeon Warner
Bi-weekly calls (see below):
- Announce on #general and #discovery
- Public notes in Google Drive: https://drive.google.com/drive/folders/1Un3ALFr1zKROYr9b6h5VGX4Xikz6SqQC
- Topics seeded in advance, with a few key speakers drawn from community, then discussion
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

Calls and topics

Calls bi-weekly, Tuesdays, 9am PT / 12noon ET, 5pm UK, 6pm CET, (Note Zoom URL has been changed, and will now be stored in the meeting document )

Calls are expected to continue through the length of the grant and hopefully beyond.

Discussion materials and references (e.g. slides, documents, etc.)

Knowledge panels
- Running slide deck of examples
- Spreadsheet reviewing (1) data we would like to include and (2) data we have now (started by Steven Folsom with contributions from others)
- Data Sources for Knowledge Panel (Hilary Thorsen)
- Zotero references (Dan Scott)
Index time processes
- Architectural/search index review of when/how to integrate data (Michael Gibney)
User stories and usability
Browsing, search, and open-ended discovery
- Running slide deck of examples
- Search demo incorporating Wikidata and LOC content
  - https://github.com/thisismattmiller/wiki-knowledge-panel
  - https://thisismattmiller.github.io/wiki-knowledge-panel/ (Matt Miller)
- Searching across libraries and reconciling information between LC authorities/subject headings and Wikipedia
  - Forward to Libraries and integration in online books site
  - LC mapping to Wikipedia dataset
Data analysis
- Data and Discovery
- Wikidata queries for discovery (Steven Folsom)
- University of Chicago ShareVDE/OCLC analysis: Report, Presentation
- Running list of data sources with brief summary (Collaborative)
- See also spreadsheet reviewing data to include and data sources under knowledge panels section above
Overview of questions at different levels (data, index, interface)
Additional references
- LD4 Conference Presentations : http://bit.ly/ld4pres with discovery blocks on May 10
- LD4 Conference birds of a feather discussion

Possible future call topics

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...

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