Deutsch

JUN 21

DevConnect 2022: How MARC can SPARQL!

This presentation takes the skills and tools adopted by libraries for dealing with linked data and applies those methodologies, focusing primarily using RDF and SPARQL, and proposes their suitability in retrospective analysis of existing MARC data.

On-Demand-Veranstaltung.

Featured presenters: Kirk Hess, OCLC; Jeff Mixter, OCLC

Analyzing MARC data for quality assurance can be a challenging task. Libraries are pivoting to linked data structures, seeking to capitalize on the opportunity to create and provide more interoperable data that can help improve the end-user search and discovery experience. While many user-supporting value propositions of linked data are by now well-characterized, linked data approaches can also be employed for analyzing MARC data in ways that are more efficient and streamlined. This presentation takes those skills and tools adopted by libraries for dealing with linked data and applies those methodologies, focusing primarily using RDF and SPARQL, and proposes their suitability in retrospective analysis of existing MARC data.  The presentation will start with an overview of the project and will conclude with live demonstration of the techniques used.

This virtual event will be recorded and posted in the OCLC APIs Community. All registrants will be sent a link to the recording after the event.

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This session is part of DevConnect 2022, an annual OCLC program in which OCLC and library staff share API and technology insights with the library community.

Aufzeichnung ansehen

Datum

21 Juni 2022

Uhrzeit

11:00 AM – 12:00 PM
Eastern Daylight Time, North America [UTC -4]

Recording access

This webinar recording is available to members of the OCLC APIs Community. To view the recording, you’ll need to sign into the OCLC Community Center with your credentials. If you don’t know your Community Center credentials, reference the OCLC Support website or contact OCLC Support.  If you don’t have Community Center credentials, you may request them here.