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dc.contributor.authorClark, Jason A.
dc.contributor.authorRossmann, Doralyn
dc.date.accessioned2018-05-11T21:06:26Z
dc.date.available2018-05-11T21:06:26Z
dc.date.issued2017
dc.identifier.citationJason A. Clark & Doralyn Rossmann (2017) The Open SESMO (Search Engine & Social Media Optimization) Project: Linked and Structured Data for Library Subscription Databases to Enable Web-scale Discovery in Search Engines, Journal of Web Librarianship, 11:3-4, 172-193, DOI: 10.1080/19322909.2017.1378148en_US
dc.identifier.issn1932-2917
dc.identifier.issn1932-2909
dc.identifier.urihttps://scholarworks.montana.edu/xmlui/handle/1/14531
dc.description.abstractToday's learners operate in digital environments which can be largely navigated with no human intervention. At the same time, libraries spend millions and millions of dollars to provide access to content which our users may never know is available to them. Through the Open SESMO (Search Engine & Social Media Optimization) database project, Montana State University (MSU) Library applied search engine optimization and structured data with the Schema.org vocabulary, linked data models and practices, and social media optimization techniques to all the library's subscribed databases. Our research shows that Open SESMO creates significant return-on-investment with substantial increased traffic to our paid resources by our users as evidenced through analytics and metrics. In the core research of the article, we take a quantitative look at the pre/post results to assess the Open SESMO method and its impact on organic search referrals and use of the collection analyzing data from three distinct fall semesters. Returns include demonstrated library value through database recommendations, connecting researchers to subject librarians, and increased visitation to our library's paid databases with growth in organic search referrals, impressions, and click-through rates. This project offers a standard and innovative practice for other libraries to employ in surfacing their paid databases to users through the open web by applying structured and linked data methods.en_US
dc.language.isoen_USen_US
dc.publisherTaylor & Francisen_US
dc.subjectResearch Subject Categories::TECHNOLOGY::Information technologyen_US
dc.titleThe Open SESMO (Search Engine & Social Media Optimization) Project: Linked and Structured Data for Library Subscription Databases to Enable Web-scale Discovery in Search Enginesen_US
dc.typeArticleen_US
mus.citation.extentfirstpage172en_US
mus.citation.extentlastpage193en_US
mus.citation.issue3-4en_US
mus.citation.journaltitleJournal of Web Librarianshipen_US
mus.citation.volume11en_US
mus.identifier.categoryEngineering & Computer Scienceen_US
mus.identifier.doi10.1080/19322909.2017.1378148en_US
mus.relation.collegeLibraryen_US
mus.relation.departmentLibrary.en_US
mus.relation.universityMontana State University - Bozemanen_US
mus.contributor.orcidClark, Jason A.|0000-0002-3588-6257en_US
mus.contributor.orcidRossmann, Doralyn|0000-0002-6490-4223en_US


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