1 / 29

Metadata out of control

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 .

mei
Télécharger la présentation

Metadata out of control

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Metadata out of control Network-level metadata aggregations Titia van der Werf Strasbourg, 26 february 2013

  2. From local catalogues ... http://old-photos.blogspot.nl/2011_01_01_archive.html ... to large metadata aggregations. http://upload.wikimedia.org/wikipedia/en/1/1e/T%26T_Supermarket.jpg

  3. http://www.theeuropeanlibrary.org/confluence/display/wiki/A+Library+domain+aggregatorhttp://www.theeuropeanlibrary.org/confluence/display/wiki/A+Library+domain+aggregator From an infrastructure of aggregators ... ... to the web of data tapestry. Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/

  4. Taking a closer look at the emerging web of data tapestry

  5. Where are the libraries and archives in the Web tapestry?

  6. 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)

  7. 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 ...

  8. 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

  9. “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

  10. 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

  11. e-logistics in the web tapestry: who is doing what?

  12. Rule 3: Libraries = push quality data to the front-end of the Web Which data are important?

  13. The 4 Ws: what, who, where, when

  14. 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

  15. Data quality: Europeana/OCLC • Who: matching to VIAF • What: clustering similar items (reconstructing books and archival collections) • Where: landing page institutional website

  16. 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.

  17. 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

  18. Quality of the system is only as good as the quality of the data

More Related