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Librarians' adventure into LODLAM Silvia Southwick & Cory Lampert UNLV Digital Collections LODLAM Training Day August 19, 2014 San Jose, CA

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Presentation titled Librarians' adventure into LODLAM by Silvia Southwick & Cory Lampert during the SemTech LODLAM Training, San Jose, CA, August 19, 2014

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Page 1: Southwickc lampert lodlam_training

Librarians' adventure into LODLAM

Silvia Southwick & Cory LampertUNLV Digital Collections

LODLAM Training DayAugust 19, 2014San Jose, CA

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Agenda

• How the adventure started• UNLV Linked Data project• Technologies used for transforming metadata into linked

data• Visualizations of linked data (demos)• Next steps and Q & A

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• Pivot ViewerC:\Users\Silvia\Desktop\videosCNI\PivotViewer.mp4

Example of linked data visualization

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How we started (2012)

• UNLV Libraries study group• Literature Review• Survey of technologies• Experimentation• Design of a project

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Why? Examples of current records

Showgirls Menus

Dreaming theSkyline

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title

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Making the Case for Linked Data

Problem: – Rich metadata is being lost when adopting a standard that is

designed for interoperability (Dublin Core)

– Rationale for adopting linked data is being disseminated, but there is very little practical implementation to serve as reference

– Evolving beyond records takes resources and requires embracing an exciting but unknown future

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UNLV Linked Data Project

Goals: • Study the feasibility of developing a common process that

would allow the conversion of our collection records into linked data preserving their original expressivity and richness

• Publish data from our collections in the Linked Data Cloud to improve discoverability and connections with other related data sets on the Web

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Main Concepts / Technologies

CONCEPTS• URIs• Triples• RDF• HTTP Protocol• Triplestores• SPARQL

Technologies• Digital Asset Management

(CONTENTdm)• OpenRefine • Karma (hierarchical data structure)• Mulgara / OpenLink Virtuoso• SPARQL end points

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Actions Technologies

Prepare dataExport data

Import dataPublish

Open Refine

Mulgara /Virtuoso

CONTENTdm

Import dataClean dataReconcileGenerate triplesExport RDF

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title

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Phase 1

• Clean data

• Export data

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Clean / Export Data

Technology: CONTENTdm• Increase consistency across collections: – metadata element labels– use of well-known CVs– share local CVs– etc.

• Export data as spreadsheet

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OpenRefine

• Open source

• It is a server – can communicate with other datasets via http

• Open Refine and its RDF extension should be installed

Screenshots to show some of the functions we have used

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Import

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Facets

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Split multi-value cells

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Facet view forGraphic Elementsafter splitting

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Reconciliation

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Specifying Reconciliation service

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Activating Reconciliation

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Mapping between Showgirls and EDM

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Implementing Mapping (Skeleton)

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Exporting RDF files

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Actions Technologies

Prepare dataExport data

Import dataPublishQuery

Open Refine

Mulgara /Virtuoso

CONTENTdm

Import dataClean dataReconcileGenerate triplesExport RDF

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Phase 3

• Import data• Publish• Query

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Mulgara Triple Store: Import

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Simple SPARQL query

Select *

Where {?s ?p ?o} limit 100

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Visualization Open Source Tools

• OpenLink Virtuoso Pivot Viewer

• RelFinder

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• Good for displaying images

• Selection of images through SPARQL Queries

• Allows refinements using facets

• Allows creating dynamic “collections”

OpenLink Pivot Viewer

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SPARQLQuery

Costume DesignDrawings

Showgirls

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• Link to the demo: C:\Users\Silvia\Desktop\videosCNI\PivotViewer.mp4

Example of Pivot Viewer

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Examples of RelFinder

• Good to show relationships:– Among people – Among “things”

• Show type of relationships

Demos:– African American Experience in Las Vegas (Oral History): C:\

Users\Silvia\Desktop\videosCNI\AAE_relationships.mp4 – Cross collections people relationship: C:\

Users\Silvia\Desktop\videosCNI\Frank_relationships.mp4

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Next steps for the UNLV project

• Transform all digital collections into linked data• Increase linkage with other datasets• Publish as Linked Open Data• Design and assess user friendly interfaces • Work on integrating data from diverse local systems• Produce a cost benefit analysis to inform future plans for the

development of digital collections

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Our Experience

• Project led, implemented and managed by two busy faculty librarians

• No model to follow; our model was experimentation and research

• With interest and motivation, Linked Open Data is a feasible goal

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Thank You!Questions?

Cory LampertHead, Digital [email protected]

Silvia SouthwickDigital Collections Metadata [email protected]

UNLV’s Linked Open Data Blog: http://library.unlv.edu/linked-data