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Linked Open Data for Subject Discovery: Assessing the Alignment between Library of Congress Vocabularies and Wikidata

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Abstract

Linked open data (LOD) has long been touted as a means to enhancing discovery of library resources through the use of robust links between related items and concepts. Recently, libraries have begun to experiment with LOD sources such as Wikidata and DBpedia to harness usercontributed resources and enhance information displayed in library discovery systems. The Michigan State University Libraries (MSUL) Digital Repository Team has embarked on a project to display contextual information from Wikidata and DBpedia in "knowledge cards" (informational pop-up windows) alongside subject headings with the goal of providing users with more information on items in the digital repository. This paper will briefly describe this project and outline a quality analysis initiative meant to evaluate linkages between Library of Congress Subject Heading (LCSH) and Wikidata as well as the results of this analysis. It will also address a number of challenges encountered in terms of mapping between different controlled vocabularies. Finally, it will conclude with possible next steps for improving the accuracy of knowledge cards and the LOD that supports them.

Author information

Eunah Snyder
undefined, USA
Lisa Lorenzo
Michigan State University Libraries, USA
Lucas Mak
Michigan State University Libraries, USA

Cite this article

Snyder, E., Lorenzo, L., & Mak, L. (2020). Linked Open Data for Subject Discovery: Assessing the Alignment between Library of Congress Vocabularies and Wikidata. International Conference on Dublin Core and Metadata Applications, 2020. https://doi.org/10.23106/dcmi.952141577

DOI : 10.23106/dcmi.952141577

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