Digging into Linked Data: Perspectives from the Long Tail

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Presentation transcript:

Digging into Linked Data: Perspectives from the Long Tail Paromita Biswas, Western Carolina University (WCU) Andrea Leonard, Appalachian State University (ASU) Texas Conference on Digital Libraries 2018

Belk Library & Information Commons, ASU Hunter Library, WCU

Choosing the dataset: WCU No. of items Oldest and most extensive collection on Appalachian culture and heritage Number of items for project: 25

Choosing the dataset: ASU Number of items for project: 20 Quilts found in: University Library Art Collection ASU Historical Photos Kirby and Eller Family Letters

Learning Curve: Concepts Mapping Data Models/Mapping Europeana Data Model: ProvidedCHO (core class) and its properties (EDM provides the option to map to Dublin Core terms) Resource Description Framework (RDF) Data in triple statements Literals and URIs 5 star data Dereferenceable URIs/Reuse URIs RDF Serialization: Turtle-Terse RDF Triple Language Easily readable and could be manually written See: *Silvia B. Southwick, A Guide for Transforming Digital Collections Metadata into Linked Data, Journal of Library Metadata (2015) *Heath and Bizer, How to Publish Linked Data on the Web *Sauermann et al. Cool URIs for the Semantic Web (2006)

Learning Curve: Tools Getting the data ready; uploading to OpenRefine Adding the RDF extension and reconciliation services Reconciling controlled vocabularies with established URIs (LCNAF/LCSH/VIAF/Getty/DBPedia/Wikidata) See: *Verborgh and De Wilde’s Using OpenRefine (2013) *Hooland and Verborgh, Linked Data for Libraries, Archives and Museums (2014) Edit RDF Skeleton (RDF Schema Alignment) creating the URI for the ProvidedCHO: <Namespace><class of thing described>/<local unique ID> Inventory no./Omeka no. Triple stores and SPARQL Apache Jena Fuseki/practice querying Apache Marmotta/visualization Querying RDF/linked data with SPARQL *Certificate in XML and RDF-Based Systems (Library Juice Academy)

Tools--RDF Skeleton

RDF Preview (Skeleton)

Fuseki

Querying the data

Graphs/Relationships https://www.w3.org/RDF/Validator/

Current Project Status

Data Views generated by Apache Marmotta Graphical representation of data: Graph of the “graphs” Types of classes “Contexts” (“graphs” in SPARQL): The triple containers with their own URI

Hope versus reality: Will we be able do with this with Apache Marmotta…? Manual visualization via Darrin J. Ward’s Mapping Tool https://www.darrinward.com/lat-long/

Challenges Overall Time gaps & work loads Learning curves & training Metadata cleanup Moving landscapes Institutional growth angst Challenges with systems

Benefits Theoretical to practical Open source technologies Collaboration and connections Groundwork for future projects

Next Step(s) PHASE TWO

Thank you! Tom Bennett, Operations & Systems Analyst: Apache Marmotta setup Scott Goldstein, Web Librarian: giving SPARQL queries for visualization a try