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Radically Open Cultural Heritage Data on the Web


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What happens when tens of thousands of archival photos are shared with open licenses, then mashed up with geolocation data and current photos? Or when app developers can freely utilize information and images from millions of books? On this panel, we'll explore the fundamental elements of Linked Open Data and discover how rapidly growing access to metadata within the world's libraries, archives and museums is opening exciting new possibilities for understanding our past, and may help in predicting our future. Our panelists will look into the technological underpinnings of Linked Open Data, demonstrate use cases and applications, and consider the possibilities of such data for scholarly research, preservation, commercial interests, and the future of cultural heritage data.

Published in: Education

Radically Open Cultural Heritage Data on the Web

  1. 1. this is the story ofmaking some openlinked* data*disclaimer: it’s not very linked yet
  2. 2. we had a little project in York ...
  3. 3. to expose ‘The London Art World 1660-1735’ dataset - several years of history of art research trawling primary and secondary sources of information about into art sales,people, places and artworks all contained in spreadsheets
  4. 4. simple database-driventhis is about an art sale web site first we put the data on the web
  5. 5. ok, so it’s on the web, it has some links, it’s open, right? can I gonow? ... not so fast, I’m not done yet
  6. 6. how does a machine know and these are links to info about that this is about an art people and places? sale? and how can someone get at this info and do like enrich it with interesting things with it? information from elsewhere?
  7. 7. linked open data ... describing real-world things andthe relationships between them in a machine-readable way
  8. 8. in walks RDF:Resource (identifying resources on theweb) Description (and describing them) Framework (with a model based on triples and graphs)
  9. 9. PREDICATESUBJECT (aka relationship) OBJECT <someArtist> <occupied> <somePlace> <someArtist> <painted> <somePainting> <somePainting> <soldIn> <someSale> <someSale> <happenedIn> <somePlace> all of these <someCatalogue> <describes> <someSale> will be uris <someSaleItem> <soldFor> <somePrice> RDF - <someBuyer> <purchased> <someSaleItem> all this is not about the rdf you are looking triples for
  10. 10. an ontology standardized representation is a of knowledge as a set of concepts within a domain, and the relationships between those concepts. It can be used to reason about the entities within that domain, and may be used to describe the domain (wikipedia)or, put another way “a standard way of describing stuff for a given domain” (me)
  11. 11. we should either use terms fromexisting ontologies or create andpublish our terms using standard approaches
  12. 12. we created an event-driven ontology based on DUL (DOLCE Ultra Lite) and LODE (Linked Open Events) why? because we wanted to create rich andspecific data but ensure our data could stillbe understood in a generic and low barrier way
  13. 13.
  14. 14. linking means makingconnections between our data and others
  15. 15. we linked our people to viaf and some of our places to geonames ... <ourPerson> <sameas> <viafPerson> <ourPlace> <sameas> <geonamesPlace>... a data consumer can start following this network of links
  16. 16. making data
  17. 17. image:
  18. 18. spreadsheet cleanup with scripting, a database and some Google refine action* * google refine is very useful for dealing with messy spreadsheets + has an rdf plugin
  19. 19. a turtle* document for each of our 38,000 primary ‘entities’ sale person place artwork source stored in and indexed in** semantic search engine * a format for creating rdf data ** try a search for sale
  20. 20. foaf:primaryTopic <>; rdf:type foaf:Document, dctype:Text . <> void:inDataset <>; rdf:type foaf:Document, dctype:Text . <> void:inDataset <>; rdf:type foaf:Document, dctype:Text . <> mapping:hasResearchID "3.0548"^^<xsd:string>;SUBJECT rdfs:label "The Green Doors in the Little Piazza, Covent Garden; sale venue"; vocupper:hasPlaceName "The Green Doors in the Little Piazza, Covent Garden"; vocupper:hasBuildingName "The Green Doors"; vocupper:hasStreetName "Little Piazza"; vocupper:hasCity "London"; vocupper:hasCounty "Greater London"; vocupper:hasCountry "England"; vochoa:hasContributorOfSource "Richard Stephens"; OBJECT oactxt:venueOfSale < 8>;PREDICATE oactxt:venueOfSale <>; oactxt:venueOfSale <>; oactxt:venueOfSale <>; oactxt:venueOfSale <>; vocupper:liesWithin [ owl:sameas <>; rdf:type model:Place, vocupper:Country, LINKED owl:NamedIndividual ]; rdf:type model:Place, owl:NamedIndividual .
  21. 21. DISCLAIMER ours was one approach it is very experimental and is imperfect in various waysit showed that we could do linked data with an existing system we want to do more
  22. 22. linked open data is leap of faith - you have to expose databefore people can consume data
  23. 23. aim high -if we all put out high quality rich data we can do high quality AND low barrier things with it
  24. 24. there are 77981 results for ‘York’ in geonames we had a little project in York ...
  25. 25. we had a little project in ...
  26. 26. credits Richard Stephens: data creator Tate: data partners Martin Dow: ontology dev Stephen Bayliss: ontology dev Paul Young: data transform LOCAH project: inspiration Jon Voss: lodlam guruUniversity of York: institutional support JISC: funding @julieallinson #LODLAM #sxsw