Funding + Scope
The project was initiated with funding from an Innovation Grant from the University of Illinois Library to explore transforming MARC records to BIBFRAME linked data. The proposal is available here.
The project team chose to focus on the corpus of e-book records in the library catalog. The Illinois Library provides access to nearly 300,000 e-books.
By the end of the Summer 2015 semester the team completed the e-book work and two sample search interfaces demonstrating the feasibility of transforming & enriching MARC records with linked open data, and demonstrating approaches in retrieval of the records for enhanced discovery. Final Report available at: http://goo.gl/Azjxkt
The team included librarians Qiang Jin (CAM) and Jim Hahn (UGL), as well as two graduate students: Gretchen Croll (GSLIS), and Suma Vangala (CS).
We collaborated broadly and sought input from multiple metadata experts in the library, including Micheal Norman and Ayla Stein.
The BIBFRAME @ Illinois Project is registered with the Library of Congress BIBFRAME implementation Register.
BIBFRAME Search Options
Google Custom Search: Structured Data
This search interface provides results with structured data when retrieving BIBFRAME records.
E-book Bento view
A pilot implementation of how BIBFRAME records are retrieved in a Bento-style seach.
Sitemaps for BIBFRAME HTML
As a result of the transformation process, there are twenty-nine HTML sitemaps, with 10,000 pages per map available for parsing here.
Each HTML file (a BIBFRAME record) encorporates RDF for a BIBFRAME Work, Instance, Authority, and Annotation.
BIBFRAME HTML also incorporates Schema.org structured data.
Presentation: Tools for Enhanced Discovery on the Web
Hahn, J., Jin, Q., "Tools for Enhanced Discovery on the Web," American Library Association Annual Conference, Cataloging and Metadata For the Web: Meeting the User Where They Are Pre-conference, Chicago, IL: Friday, June 23, 2017.
Code + Acknowledgements
For BIBBFRAME 1.0 research and development in 2015 we utilized the Library of Congress XQuery transformation code to begin our process, and then augmented the results by programmatically enriching records with linked open data. Python code developed as a result of the grant is available from Bitbucket.