Session recording (Picknally Camden & Hahn; Khan & Usong)Prototyping and Evaluating the Share-VDE (Virtual Discovery Environment) Linked Data Discovery Interface, Beth Picknally Camden and Jim Hahn (University of Pennsylvania)
The
Share-VDE (Virtual Discovery Environment) has engaged a global partnership, with library-driven development.The project encompasses enrichment and conversion from MARC to BIBFRAME/RDF, creation of a cluster knowledge base, development of manual and automated tools for interacting with data, and the creation of a linked data discovery environment. University of Pennsylvania Libraries have been a Share-VDE partner since its inception in 2016, and, in 2019, embarked on a special project with Casalini, @Cult and Samhaeng for further development on the user interface. Penn’s goals are to demonstrate discovery in a linked-data user environment, and to enhance usability with APIs that will allow users to find resources and request delivery (local or ILL). This presentation will focus on the process for developing the prototype (UX/UI design, mock-up, technology review, etc.) and include a demo of the prototype. Additionally, we will articulate a set of interface evaluation metrics in the form of a heuristic research agenda for linked data discovery. The research provides an understanding of the capabilities of the Share-VDE interface to support the user tasks promulgated in the IFLA Library Reference Model (LRM).
The library catalog and linked data: a tale of two technologies, Huda Khan (Cornell University), Astrid Usong (Stanford University)
In the Linked Data For Production: Pathway to Implementation (LD4P2) project, we employed a user-centered approach to explore the integration of linked data sources in library discovery interfaces Through a combination of user interviews and evaluations of mockups and prototypes, we sought to better understand how linked data can meet user needs around search in the library catalog that extend beyond known-item search to more open-ended discovery tasks. We have also investigated concrete approaches for using Schema.org to improve the indexing of our catalog records by search engines. In this session, we review our design and prototyping efforts, Blacklight integration work, and the user research and evaluations we have conducted to address the four main discovery areas laid out in the LD4P2 grant: knowledge panels, browsing, semantic search, and the use of Schema.org. We will discuss the larger questions of intended user experience and delve into what we learned from users about our mockups and prototypes incorporating context, suggestions, and relationships to subjects, people, and collections. We will also discuss specific challenges and lessons learned while developing Blacklight prototypes bringing in data from both linked data sources such as Library of Congress name and subject authorities, Wikidata, DbPedia, FAST, and VIAF; as well as from external sources such as Who's on First, Discogs, Google Books search, the Open Syllabus Project, and Cornell Digital Collections. Some challenges for integrating data from non-catalog sources include inconsistent availability of connections between catalog entities and linked data sources, consistency and comprehensiveness of the data, reliability, and the performance of queries or data retrieval. We will also discuss possible future directions for improving user experience and integrating this work into Blacklight.
Book actions and Linked Bibliographic Data at Google, Erin Dobias (Google) (
This presentation will not be recorded.)Over the last few years Google has worked on exposing library holdings for ebooks, audiobooks, and print books in both Knowledge Panels and on the new books.google.com, allowing users to explore the holdings at their local library and discover formats that they may not have previously considered. In this presentation, I will discuss how this data is exposed, and how the increased exposure has driven the need for Work IDs, work/manifestations relationships, and manifestation/manifestation relationships in bibliographic data.
