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*Apologies for cross-posting* Please join us for three exciting presentations describing linked data projects. After our speaker presentations, the group will have an opportunity for questions and discussion. Don't forget to add it to your Conference Scheduler <https://eventscribe.com/2019/ALA-Midwinter/fsPopup.asp?Mode=PresInfo&PresentationID=470351> ! Time: Saturday, January 26, 8:30-10:00 AM Location: Washington State Convention Center, TCC-Yakima 1 *1. "Practical Linked Data Implementation: Trail of the Caribou"* Based on data collected by the Trail of the Caribou Research Group on Royal Newfoundland Regiment soldiers in WWI, this presentation will focus on a practical implementation of Linked Data. After a brief review of Linked Data and the technology stack that supports it, demonstrations will include a basic SPARQL query of a web-based endpoint; building a more complex SPARQL query to retrieve data from multiple sources; remotely querying, retrieving, and combining Linked Data using Apache Jena at the command line; and updating a local triplestore with remote data utilizing Apache Jena Fuseki. Bio: Heather J. Pretty is Cataloguing Librarian at Memorial University in Newfoundland & Labrador, Canada. *2. "Enhancing Subject Access on a Shoestring: Subject Knowledge Cards Built on Linked Open Data"* With different library and non-library entities publishing their thesauri in linked open data and linking them to one another, an enhanced subject discovery experience through linked data is no longer a pipe dream. Starting with a FAST (Faceted Application of Subject Terminology) URI in a MODS record, this presentation will demonstrate how to utilize linked open data sets from OCLC FAST, Wikidata, DBpedia, and MeSH (Medical Subject Headings) to create subject hierarchy browsing; provide contextual information of the subject term in context; and allow discovery of related items in A&I (abstracting and indexing) databases and the library catalog. Using AJAX to make live queries to several APIs allows us to load subject data dynamically and asynchronously, generating subject knowledge cards on the fly without caching the returned data locally. This presentation will also evaluate the benefits and limitations of building linked data features that rely on live data from several interconnected sources. Bio: Lucas Mak is Metadata and Catalog Librarian at Michigan State University Libraries (MSUL). He supervises a small team of metadata librarians and oversees non-MARC metadata creation and maintenance for the MSUL digital repository. Besides non-MARC metadata, he has experience in traditional cataloging with a specialty in audio-visual materials. He is the NACO coordinator for MSUL and coordinator for the Michigan NACO Funnel. In recent years, his work has been focusing on workflow automation, large-scale metadata manipulation and enrichment, and experimental linked data projects. *3. "Publishing Static Library Linked Open Data"* We need a model for publishing linked data when we don't have linked data services like content negotiation, a triple store with a friendly user interface, or a SPARQL endpoint. Our publishing model is a step toward establishing a practice for publishing static library linked open data. It requires a method for minting IRIs locally as hash DOIs; care must be taken to ensure all local IRIs dereference and are persistent. The raw data, once scrubbed, is mounted on a web server in multiple serializations, all constellations to the dataset landing page modeled as HTML+RDFa. Appropriate steps are taken to optimize discoverability by search engines, and human users should see the HTML landing page and not just raw data. The data is broken into multiple files based on entities in our data models. Attempts are made to bring the datasets under version control. Bio: Theo Gerontakos is a Metadata Librarian at the University of Washington in Seattle. He has been a Metadata Librarian since 2001. Since 2013, at UW, he has led several linked data teams working on linked data projects. From 2012-2014 he was Co-Chair of ALA's LITA/ALCTS Linked Library Data Interest Group. Sincerely, LLD-IG Scott Carlson and Craig Boman Co-Chairs