Implementing Linked Art in a Multi-Modal Database for Cross-Collection Discovery

Abstract

Yale University has implemented a knowledge graph based discovery system that brings together the various art, natural history, archival, conservation and bibliographic collections using Linked Open Usable Data standards such as Linked Art and IIIF. This system comprises more than 41 million records, which would expand to more than 2 billion RDF triples, and is thus at a similar scale to Europeana. This paper presents the lessons learned from the five year effort around the usability of linked data structures across the organization, the technologies needed to make use of the knowledge in a performant way, and the appropriate design paradigms for front end applications which make the graph easily and intuitively accessible to researchers and the public, including the necessity of consistency in data modeling, that records are an essential concept to maintain through multi-modal systems, and the use of hypertext and web caches to maintain the separation between systems.