Starting in May 2024, Primo users are able to unlock a world of enriched information through Linked Open Data integration, enabling patrons to effortlessly delve deeper into the lives, works and legacies of notable figures across disciplines. From seamlessly exploring person entities with intuitive autocomplete during searches, to revealing "info cards" on the full record pages and exploring extensive "person pages" that aggregate authoritative details from trusted external sources and the library catalogue.

In parallel, Alma now supports the use of BIBFRAME records (Work and Instance) throughout the system. From acquisition to resource management, fulfillment and all the way through to Discovery systems. This is in addition to supporting the enrichment of existing MARC records with URIs in a simple and configurable way. BIBFRAME support is the first step of our joint community vision for Linked Open Data in libraries and supporting multiple Linked Open Data metadata formats.

TJ Kao, Head of Metadata Creation at University of California, Davis has agreed to share the experience of being the first customer to catalog in BIBFRAME in production.

"We are now able to use Alma and Primo to show the great potential in Linked Open Data, and at the same time, have very minimal disruption to our users, from the Primo side. We are confident that this transition from a MARC environment to a linked open data environment, is possible and is totally feasible."

"There is an opportunity for us to really work with a vendor to develop something that's going to work for everyone."

Ex Libris has been working for the past year with the library community in a linked open data focus group, bringing Alma and Primo VE to be production-ready to support BIBFRAME works and instances. UC Davis has been one of the leading institutions in developing linked open data and has been part of Ex Libris' linked open data community of practice for many years.

Linked open data has the potential of simplifying cataloging, creating a network of linked entities and the possibility of more accurate and curated information. It also improves existing workflows, such as clustering similar records together based on IDs (URIs) and not only relying on text-based matching.

Linked open data is also high-quality data that can serve as a reliable infrastructure for AI in various scenarios, such as extracting information, creating more relations, and using AI for insights from a linked data network.

Ex Libris Linked Open Data pillars focus on better discoverability, collaborative cataloging and global interoperability, supported by community engagement and advanced technology.