VRA 2014 Brave New World Cataloging, Mixter


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Presented by Jeffrey Mixter at the Annual Conference of the Visual Resources Association, March 12-15, 2014 in Milwaukee, Wisconsin.

Session 11, Brave New World Cataloging: Using RDF and Linked Open Data for the Semantic Web
ORGANIZER: Sheryl Frisch, California Polytechnic State University
MODERATOR: Trish Rose-Sandler, Center for Biodiversity Informatics, Missouri Botanical Garden
• Trish Rose-Sandler, Center for Biodiversity Informatics, Missouri Botanical Garden
• Jeffrey Mixter, Kent State University Research Support
• Georgina Goodlander, Smithsonian American Art Museum
• Patricia Harpring, Getty Vocabulary Program, Getty Research Institute

RDF (Resource Description Format) and LOD (Linked Open Data) are two key components in the ongoing development of the Semantic Web (the structured linking of web-based information to enable users anywhere to find, share, and combine information more easily). Although we are used to working in information silos much of the time, the Semantic Web can allow data to be discovered, shared and reused across application, enterprise, and community boundaries. The speakers will demonstrate how our existing data (from both VR collections and museums) can be transformed to the RDF format; how the effort can be shared in a community; and how LOD will affect and expand the tools we use daily to provide controlled vocabulary terms.

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VRA 2014 Brave New World Cataloging, Mixter

  1. 1. VRA Core as Linked Data 03-15-2014 Jeff Mixter Research Support Specialist OCLC Research mixterj@oclc.org
  2. 2. • This project evolved out of a master’s thesis project published as partial completion of an MLIS degree from Kent State University • The emergence of Schema.org as a general Linked Data vocabulary and the publication of WorldCat.org data as Linked Data served as a catalyst for the work • CIDOC CRM and the Europeana Data Model were examples of how visual resource data models could be represented using Linked Data Background
  3. 3. • Collaborative effort between Google, Yahoo, Bing and Yandex • 2011 • Serves as a general Linked Data vocabulary • 15% of Web pages use Schema.org markup • Data using Schema.org is understood and indexed by search engines as structured data • Using Schema.org has the possibility to help improve SEO • SEO in context! • SEO != Google Ranking • Search engine understanding of your structured data Schema.org
  4. 4. • Structured data drives the creation of Google Knowledge Cards • These “entity cards” are derived from structured data that Google has harvested from the Semantic Web Structured Data
  5. 5. Structured Data vs.
  6. 6. • Both of these data models have produced Linked Data representations • Both use a specialized vocabulary • The models were reviewed and consulted during the modeling/mapping process CIDOC CRM and Europeana
  7. 7. • The initial research project sought to map the VRA Core 4 model into Linked Data • Use Schema.org as the baseline vocabulary • Helps improve interoperability • Follow the Linked Data principles outlined and described by Tim Berners-Lee • Do not reinvent the wheel • Gov 2.0 Expo 2010 • The project successfully modeled the VRA Core 4 data model as Linked Data and demonstrated this by converting an existing VRA Core 4 compliant dataset (XML) into Linked Data Initial Project
  8. 8. • Linked Data model was mapped from the VRA Core 4 Restricted Schema • The model included: • 35 Schema.org terms • 1 DC Terms term • 2 VoID terms • 127 Custom VRA Core terms • Of the 127 custom terms, 88 (66%) were positioned as sub-terms of Schema.org terms • Overall 74% of the VRA Core terms were directly or indirectly mapped to Schema.org Project Results
  9. 9. • After the prototype and results were published, there was interest in using the model • The VRA Core Oversight Committee subsequently formed a Task Force to design and publish as VRA Linked Data data model • Current members: • Esme Crowles • Trish Rose-Sandler • Johanna Bauman • Rebecca Guenther • Jeff Mixter Aftermath
  10. 10. • Adapt the prototype model to create an official VRA Core data model • Using a VRA namespace! • In line with the principles of Linked Data, there will be an emphasis on mapping the VRA Core model to other Linked Data vocabularies • Schema.org • BIBFRAME • Ect. Current Project
  11. 11. • Prototype of the ontology: • http://www.essepuntato.it/lode/https://s3.amazonaws.com/VRA/ Ontology/VRA_OntologyRevised.owl • Converted a data sample for review • The model is just a prototype and we welcome comments, questions, criticism, etc. Progress
  12. 12. • Getty vocabularies are being published as Linked Data • This is very important to the micro-domain of visual/cultural heritage resources • In particular it is important to VRA since it is a standard authority recommended in the VRA Core 4 Schema • Collaboration and integration with other Linked Data models • The Semantic Web relies on interconnected datasets/models • Data silos are bad Future Potential
  13. 13. ©2013 OCLC. This work is licensed under a Creative Commons Attribution 3.0 Unported License. Suggested attribution: “This work uses content from [presentation title] © OCLC, used under a Creative Commons Attribution license: http://creativecommons.org/licenses/by/3.0/” Thanks! Question?