The use of linked data within a traditional library catalog is the key to broader implementation of linked data within the academic library community. Without a concrete demonstration of the benefits of linked data, administrators are reluctant to commit the time, effort, and funds for the transition from MARC. LD4P2 will enhance the Blacklight open source search engine with linked data features, such as (1) knowledge panel in search results to present contextual information powered by linked data; (2) browsing based on authority files and links to related entities in external data; (3) 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 (4) microdata on item pages to enable machine crawling.
Partner institutions involved in this area of the grant have individually and collaboratively worked on the usability and user interface design questions around the use of linked data in discovery. We have also been experimenting with prototypes and development to better understand how the integration of linked data can be implemented and what are the resulting possible user interactions. Discussions and participation in the LD4 Discovery Affinity Group have also led to fruitful conversations and refinement of grant-related work. The Blacklight LD Working Meeting is another collaborative community effort to which we hope to contribute and from which we hope to garner additional ideas for further work.
Grant (overall) questions/discussions
Articles/related work review (library catalog design and linked data interfaces)
User interviews (mix of researchers/faculty) (Astrid Usong )
Knowledge Panel Guerilla testing and results (focusing on students) (Astrid and Ally)
Also see Discovery Affinity Group page (referenced below)
Cornell
KPAOW! (Knowledge Panels Area Of Work)
Mockups for evaluation - thank you Astrid Usong !!
Stanford
Blacklight has hundreds of installations worldwide and particularly deep adoption in North American research libraries, and in conversations at ALA Midwinter 2018 about the next phase of LD4P, Blacklight discovery captured the imaginations of a number of libraries.
Potential discovery enhancements to Blacklight include (1) knowledge panel in search; (2) browsing based on authority files and links to related entities in external data; (3) semantic search; and (4) microdata on item pages to enable machine crawling.
Items 1 (knowledge panel in search results to present contextual information powered by linked data) and 4 (microdata) have proven implementations in other discovery environments, and will be the first targets for development.
Item 2 (browse) offers the richest potential benefits to users. This effort will require balancing the capabilities of the data, user needs, design of an intuitive and useful interface, and technical constraints of current technologies. Challenges and questions around designing and implementing an effective browse experience include:
Item 3 (semantic search) also has promise, though the best examples of semantic search happen in more tightly scoped information domains (such as medical search using MeSH). Analysis and experimentation will be required to see if subject searches and headings will lend themselves to a semantic approach in a general catalog environment. We intend to explore geographic search as a first and promising entry point to this approach. Analysis will include how patrons interact with the library catalog, especially for subject searches and searches resulting in zero results, to create a better, user-centered design; log analysis of current searches, as well as data analysis to determine what search arguments could be transformed to alternative searches with richer results using linked data. It will also include exploring technical approaches to semantic search, including adding semantically-related terms at index time, leveraging dynamic look-ups of linked terms via external services, and performant approaches to including semantic type-ahead / autosuggest of search terms.
This analysis and experimentation will be done by a team combining user experience designers, metadata experts, and software engineers. Design and development will happen in an iterative manner as the group explores objectives and possible approaches; trials implementation; assesses effectiveness; and refines for better results.
Development of the Blacklight enhancements will be supported by the developers, UX designers and technical services at Cornell and Stanford. The development of semantic search and browse mechanisms, including visualizations where useful, will be supported by the Iowa team.