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Electronic Services General Interest UAL Technical Services Committee

Webinar on Linked Data–June 2

Join OCLC’s Ted Fons and colleagues
for a free webinar:

Tracing the Evolution of Linked Data

An OCLC Collective Insight Event: Tracing the Evolution of Linked Data
Monday, June 2, 1:00 – 2:00 pm, Eastern Time

Five years ago linked data was introduced to the library community as a powerful technology with great promise for libraries, visionary but abstract. In the years since, what was a buzzword has become a fixture in our lexicon. Yet as our understanding of the technology has progressed and solidified, we still struggle to identify the specific benefits of linked data within our individual institutions. Join OCLC’s Ted Fons, Corey Harper of New York University, and Phil Schreur of Stanford University as they trace the evolution of linked data technology over the years, and demonstrate practical applications of the latest linked data technologies being utilized in libraries today.

Ted will introduce the topic and provide a brief overview on the evolution of linked data; Corey and Phil will dig deeper with specific examples that will help illustrate this evolution.

Corey will discuss next steps for LOD-LAM (Linked Open Data for Libraries & Museums), exploring tools and techniques to process, enrich and aggregate metadata. He will touch on recent developments, especially focused on efforts within the Hydra and Blacklight community and in the user groups for the Ex Libris product suite. Corey will give special attention to the need for use cases and experimentation.

Phil will speak on Linked Data for Libraries, a promising new grant created through a partnership among Cornell, Harvard and Stanford universities. The project goal is creation of a Scholarly Resource Semantic Information Store (SRSIS) model that works both within the individual institutions and through a coordinated, extensible network of linked open data. Phil will discuss the choice of BIBFRAME as the common data format for this project and conversion to BIBFRAME from MARC data.

Register for this webinar >>