Your SlideShare is downloading. ×
0
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Libraries and Linked Data: Looking to the Future (2)
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Libraries and Linked Data: Looking to the Future (2)

2,608

Published on

Published in: Education
0 Comments
4 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
2,608
On Slideshare
0
From Embeds
0
Number of Embeds
7
Actions
Shares
0
Downloads
30
Comments
0
Likes
4
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide
  • A lot that don’t make sense by themselves.
  • Think about our things, not in terms of fields and subfields, because it may take more than one field or subfield to represent a thing.
  • Transcript

    • 1. New bibliographic frameworkAFTER MARC: OPTIONS
    • 2. Aside: what we need to do• Identify the resources we are describing, e.g. http://lccn.loc.gov/agr52000278• Identify the data elements we are using, e.g. http://rdvocab.info/Elements/title• Identify (where possible) the information of our description, e.g. http://www.geonames.org/4984247/ann-arbor.html
    • 3. Aside: what we need to dohttp://www.worldcat.org/oclc/474017053 http://viaf.org/viaf/27068555 http://purl.org/dc/terms/creator
    • 4. RDA scenarios5editor2rev.pdf 1. Relational/object-orientedRDA Database ImplementationScenarios 2. Linked bibliographic and authority records 3. Flat file (no links)
    • 5. New bibliographicframework scenarios 1. Go nativeaccording to Coyle 2. Extract 3. Serialize
    • 6. Serialize“To put data into a particular data format thatcan be stored or transmitted.”
    • 7. Serializedc:title=“Scheduling Ourselves to Death”dc:date=“2003”dc:description=“The use of office scheduling software has led to an increase in meetings, to the point that I am definitely scheduled for meetings after retirement, and probably even after death. The fault is in the basic premise of the software: you are either in a meeting, or available to be in a meeting.”dc:creator=“Karen Coyle” key/value pairs
    • 8. Serialize<dc:title>Scheduling Ourselves to Death</dc:title><dc:date>2003</dc:date><dc:description>The use of office scheduling software has led to an increase inmeetings, to the point that I am definitely scheduled for meetings afterretirement, and probably even after death. The fault is in the basic premise of thesoftware: you are either in a meeting, or available to be in a meeting.</dc:description><dc:creator>Karen Coyle</dc:creator> XML
    • 9. Serialize{ "title": "Scheduling Ourselves to Death", "date": "2003", "description": "The use of office scheduling software has led to anincrease in meetings, to the point that I am definitely scheduled formeetings after retirement, and probably even after death. The fault isin the basic premise of the software: you are either in a meeting, oravailable to be in a meeting.", "creator": "Karen Coyle"} JSON
    • 10. MARC & MARCXML100 $a Coyle, Karen <datafield tag="100" ind1="1" ind2=" "> <subfield code="a”>Coyle, Karen245 $a Scheduling… </subfield> </datafield> <datafield tag="245" ind1="1" ind2="0"> <subfield code="a">Scheduling… </subfield> </datafield>
    • 11. MARC to RDF001 1234567100 $a Coyle, Karen245 $a Scheduling ourselves to death
    • 12. MARC to RDF1234567 100 $a Coyle, Karen1234567 245 $a Scheduling ourselves to death
    • 13. MARC to RDF 100 $a Coyle, Karenhttp://mystuff/1234567 245 $a Schedulinghttp://mystuff/123 ourselves to death4567
    • 14. MARC to RDF http://mystuff/100 Coyle, Karenhttp://mystuff/123 $a4567 http://mystuff/245 Schedulinghttp://mystuff/123 $a ourselves to death4567
    • 15. MARC to RDF http://mystuff/100 Coyle, Karen http://mystuff/123 $a 4567 http://mystuff/245 Scheduling http://mystuff/123 $a ourselves to death 4567 relationshipsubject URI “Text” URI
    • 16. “things and strings” id:1234 id:abcd id:$%^&id:3n5b “Herman Melville”
    • 17. MARC to RDF http://mystuff/100 Coyle, Karenhttp://mystuff/123 $a4567 http://mystuff/245 Schedulinghttp://mystuff/123 $a ourselves to death4567http://mystuff/123 http://mystuff/830 4574567 $vhttp://mystuff/123 http://mystuff/100 19494567 $d
    • 18. advantages disadvantages• mechanical • doesn’t change the data• doesn’t change the data • keeps library data in a• doesn’t require system library-only silo changes • doesn’t link to any data outside of libraries
    • 19. Extractdatabaseof MARC records id:1234 id:abcd id:$%^& id:3n5b “Herman Melville” “things and strings”
    • 20. What’s a “thing”?
    • 21. What’s a “thing”? Work Object PersonExpression Place FamilyManifestation Concept Corp Item Event FRBR
    • 22. National Library of Spain (BNE)
    • 23. OCLC “linked data” • Uses microformats (RDFa and schema.org) • Is embedded in the record display • Was announced June 20, 2012
    • 24. ExtractAdvantages Disadvantages• Does not require library • Isn’t visible to catalogers, so system changes no human QC• Can be re-extracted as we • Key identifiers are not part learn more of the base metadata• Isn’t visible to catalogers • Limited by what we put into records today
    • 25. “go native”• things, elements and values that have URIs• a data design that stores things and relationships• a creation interface that hides this from creators but maintains the integrity of the data
    • 26. “go native”Advantages Disadvantages• Interoperability with web • Requries replacement of resources library systems• Interoperability with intent • Difficult to make the of RDA cost/benefit argument• Possibilities for a richer library catalog, and one that does not require the user to choose between the library and the web as information resources
    • 27. … MORE THOUGHTS?

    ×