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Unleashing Expressivity Linked Data for Digital Collections Managers Cory Lampert Head, Digital Collections Mountain West Digital Library Hubs Meeting March 17, 2014 Slide 2 Agenda Why? Primer on LD for Digital Library Managers Opening our minds to a post-record world Empowering others through practical exploration Technologies Transforming metadata into linked data Lets see it! Next steps Slide 3 Linked Data Overview My collections are already visible through Google; so who cares This is a topic for catalogers Its too technical / complicated / boring Actually... Linked data is the future of the Web Data will no longer be in trapped in silos imposed by systems, collections, or records Exposed open data presents new opportunities for users Slide 4 What is Linked Data? Linked Data refers to a set of best practices for publishing and interlinking data on the Web Data needs to be machine-readable Linked data (Web of Data) is an expansion of the Web we know (Web of documents) Slide 5 Current Practice Data (or metadata) encapsulated in records Records contained in collections Very few links are created within and/or across collections Links have to be manually created Existing links do not specify the nature of the relationships among records This structure hides potential links within and across collections Slide 6 What we can do with linked data Free data from silos Expose relationships Powerful, seamless, interlinking of our data Users interact or query data in new ways Search results would be more precise Data can be easily repurposed Slide 7 Why? Our data needs an upgrade. http://5stardata.info/ Slide 8 The Linked Data Cloud Slide 9 A Post-record world Despite limitations, we have already invested lots of resources in the metadata! It is valuable. Triples represent the next evolution in powerful, flexible, standards-based interoperable metadata. Each metadata field may produce one or several statements One metadata record can produce many, many, triples Slide 10 How can we create linked data? Our metadata records are deconstructed in triples (statements) that are machine-readable Triples are expressed as: Subject Predicate - Object For example: This book has creator Tom Heath This book has title Linked Data: Evolving the Subjects, predicates and most objects should have unique identifiers (URIs) creating data that can be used in Web architecture (HTTP) These statements are expressed using the Resource Description Framework (RDF) Linked data can be queried using SPARQL Slide 11 Example of a metadata record Slide 12 Expressing metadata as triples ------------------------------------------------------------------- Slide 13 Graphical Representation Slide 14 Examples of records Showgirls Menus Dreaming the Skyline Slide 15 title Slide 16 How can I transform textual triples into machine-readable? We need a data model Europeana Data Model gives us a framework to help organize, structure, and define which predicates we are going to use Adopting an existing model is preferable to creating your own (interoperability) Slide 17 title Slide 18 Triples with URIs & EDM model predicates (Local URI) Slide 19 Machine-readable triple @prefix dc:.http://purl.org/dc/elements/1.1/ @prefix edm:.http://www.europeana.eu/schemas/edm/ @prefix foaf:.http://xmlns.com/foaf/0.1/ dc:creator http://digcol7.library.unlv.edu:8890/Agent/Las-Vegas-News-Bureau.http://digloc7.library.unlv.edu:8890/ProvidedCHO/sho000071 http://digcol7.library.unlv.edu:8890/Agent/Las-Vegas-News-Bureau foaf:depicts.http://digloc7.library.unlv.edu:8890/ProvidedCHO/sho000071http://id.loc.gov/authorities/names/n50026395 edm:hasType http://id.loc.gov/vocabulary/graphicMaterials/tgm007779.http://digloc7.library.unlv.edu:8890/ProvidedCHO/sho000071 http://id.loc.gov/vocabulary/graphicMaterials/tgm007779 Slide 20 Im a digital collections manager What is known? lots of THEORY and lots of TECHNICAL information What is happening? a move toward PRACTICE and APPLICATION in libraries by non-programmers Is there a recipe yet? - No. But, our staff CAN do significant work to prepare for linked data and to understand linked data principles, even if it isnt realistic to run a parallel process. Slide 21 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 Slide 22 ActionsTechnologies Prepare data Export data Import data Publish Open Refine Mulgara / Virtuoso CONTENTdm Import data Clean data Reconcile Generate triples Export RDF Slide 23 Export Data and Prepare Increase consistency across collections: metadata element labels use of CV, share local CVs etc. Map metadata elements with predicates from data model Export data as spreadsheet Slide 24 OpenRefine Open Source It is a server can communicate with other datasets via http Install Open Refine and its RDF extension Screenshots to cover some functions we have used so far Slide 25 OpenRefine first screen Slide 26 Slide 27 Facet Slide 28 Slide 29 Slide 30 Split multi-value cells Slide 31 Slide 32 Slide 33 Reconciliation Slide 34 Specifying Reconcilation Service Slide 35 Activating Reconcilation Slide 36 Slide 37 Creating a Skeleton Slide 38 Slide 39 Slide 40 Exporting RDF Files Slide 41 ActionsTechnologies Prepare data Export data Import data Publish Query Open Refine Mulgara / Virtuoso CONTENTdm Import data Clean data Reconcile Generate triples Export RDF Slide 42 Mulgara Triple Store: Import Slide 43 Slide 44 Simple SPARQL query Select * Where {?s ?p ?o} limit 100 Slide 45 Slide 46 Yeah, but what does it look like to humans? Pivot Viewer and Virtuoso: http://www.microsoft.com/silverlight/pivotviewer/ http://www.microsoft.com/silverlight/pivotviewer/ RelFinder: www.visualdataweb.org/relfinder.phpwww.visualdataweb.org/relfinder.php Gelphi: Linked Jazz: http://linkedjazz.org/network/http://linkedjazz.org/network/ Slide 47 Query an interface Slide 48 Slide 49 Slide 50 Slide 51 Next Steps Understand workflow for transformation of digital collections into linked data (parallel structure) Publish data; understand skills needed for best practices Increase linkage with other datasets Explore interfaces and advocate for our users; to access and display our data and related data from other datasets Collaborate and partner with others Slide 52 Thank You! Questions?