metadata out of control
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Metadata out of control. Network-level metadata aggregations Titia van der Werf Strasbourg , 26 february 2013. From local catalogues . http://old-photos.blogspot.nl/2011_01_01_archive.html. ... to large metadata aggregations . - PowerPoint PPT PresentationTRANSCRIPT
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Network-level metadata aggregationsTitia van der Werf
Strasbourg, 26 february 2013
Metadata out of control
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http://old-photos.blogspot.nl/2011_01_01_archive.html
http://upload.wikimedia.org/wikipedia/en/1/1e/T%26T_Supermarket.jpg
From local catalogues ...
... to large metadata aggregations.
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Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/
http://www.theeuropeanlibrary.org/confluence/display/wiki/A+Library+domain+aggregator
From an infrastructure of aggregators ...
... to the web of data tapestry.
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
Taking a closer look at the emerging web of data tapestry
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
Where are the libraries and archives in the Web tapestry?
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
Becoming one with the WebRule 1: the Web = the System
• Web = where our users are
• Web = an important aggregation of content
• Web = the underlying infrastructure for e-retail, e-logistics, track&trace, etc.
• Web = the metrics (clickstream)
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
The problem is not:
... that our metadata aggregations are not meeting end user needs and that we should try to get them back to our systems ...
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
Rethinking the future of the library catalogue
Thinking the unthinkable: a library without a catalogue -- Reconsidering the future of discovery tools for Utrecht University library
Simone Kortekaas at the LIBER Conference 2012
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
“Our users are on the Internet and use Google or Google-like discovery tools. They find the content they need and then expect the library to deliver the content. We concluded that if, indeed, this is the world of our users, if this is reality, (…) there really is no need for libraries to try and pull their users back to the library systems.”
http://www.libereurope.eu/blog/thinking-the-unthinkable-a-library-without-a-catalogue-reconsidering-the-future-of-discovery-to
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
Rule 2: Libraries = operate in the back-end of the Web
Separate discovery and delivery
Local catalogues and library domain metadata aggregations have become primarily known-item delivery facilities: supply aggregators.
For delivery => push location and access data to the Web via supply aggregators
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
e-logistics in the web tapestry: who is doing what?
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
Rule 3: Libraries = push quality data to the front-end of the Web
Which data are important?
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
The 4 Ws: what, who, where, when
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
Data quality: OCLC
• Who = author => VIAF
• What = work => clustering works (FRBRization and Glimirization of WorldCat)
• Where = location => Registry of Libraries; Find a Library Near You
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
Data quality: Europeana/OCLC
• Who: matching to VIAF
• What: clustering similar items (reconstructing books and archival collections)
• Where: landing page institutional website
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
Continuous quality improvement
• Looking at new data modeling solutions: Europeana (EDM), LoC (BibFrame), etc.
• Libraries are structuring systems – continuously organising and reorganising the same data.
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
Continuous quality improvement
• Wikipedia and Google are learning systems – continuously improving the data and relying on crowd sourcing for correcting and improving the quality of the data
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E U R O P E, M I D D L E E A S T & A F R I C A R E G I O N A L C O U N C I L
Quality of the system is only as good as the quality of the data