ALA Midwinter Linked Data Recordings

ala_midwinter_logo There are two Linked Data presentations from ALA Midwinter available.

The January 26th 3-4PM session Linked Data for Holdings and Cataloging: The First Step Is Always the Hardest! recording is quite good. Eric Miller (Zepheira) and Richard Wallis (OCLC) are the presenters of this linked data session.

Miller’s presentation discussed the importance of defining clear relationships; plus, more contextual information on the web will allow libraries to share their amazing collections via common search engines (holdings). He then touches on BIBFRAME and how the data model aims to be nimble enough to support the work of the past 50 years and the challenges of the next 50 years.

Wallis discussed–a vocabulary for describing webpages that was produced by major search engines. OCLC chose for their WorldCat linked data project because of’s broad adoption by the likes of Google, Yahoo! and Bing. Wallis goes on to state that while this vocabulary is not robust enough for libraries, we aren’t limited to using only one standard with linked data–they intermix.

He illustrated how the WorldCat linked data project helped make more obscure items (like dissertations) show up on the first page of a Google search. Plus, he briefly discusses the following data sets OCLC made available as linked data last year: Dewey Decimal Classification, FAST, and VIAF.

The second part of this presentation is audio, but the links associated with the speakers contain their slides. Violeta Ilik (Texas A&M University Library) & Jeremy Myntti (Head of Cataloging & Metadata Services at University of Utah – J. Willard Marriott Library) separately tried some small linked data projects using the Viewshare tool.

Viewshare is a service provided by LC for digital collections. It helps users generate and customize views (using interactive maps, timelines, facets, tag clouds) so users can interact more with the collection. Both speakers discovered some interesting trends and inconsistencies in their metadata. Good stuff!