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Building SkyNet for Science: Discovering New Frontiers Using Embedded Knowledge

From scilib, 5 months ago

Discovery in the digital environment is primarily mediated by mach more

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Slide 1: Building SkyNet for Science Discovering New Frontiers Using Embedded Knowledge Richard Akerman NISO Discovery Tools Forum March 27, 2008

Slide 6: Stanley

Slide 10: How can we better serve the machines?

Slide 11: The machines don’t speak our language

Slide 12: We must become knowledge translators

Slide 13: To Serve Machine • Produce information in formats that machines can understand, in parallel with formats that are human readable • Every web resource its machine reader • Have a limited number of formats, keep them simple, and enable easy interchange of information • Save the time of the machine

Slide 14: Bibliographic Metadata as a First Class Citizen • OpenURL (ANSI/NISO Z39.88 - 2004) • COinS

Slide 15: Tools • OCLC/Openly OpenURL Referrer • LibX • Zotero

Slide 18: Unique Identifiers • authors • institutions • text content • data

Slide 19: To Serve Human • Delicious Library • LibraryThing • Machines can process and analyze information, but only humans can use and savour information (for now...)

Slide 22: The Social Life of Humans • Formal categorization • Reviews • Ratings • Connections / Relatedness • Informal categorization (tags, folksonomies) • Use (frequency, time...) • Groups (colleagues, friends, work groups...)

Slide 23: The Social Life of Machines • Feature extraction • Similarity (count-based, vector-based) • Impact factor / PageRank • Context (location, others) • Numbers numbers numbers • Machines love unique identifiers

Slide 24: Use Case • Find me the best relevant information • Without me asking for it? • Wherever and whenever?

Slide 25: Every Book Its Reader • The WebOPAC is not a discovery interface • Build a discovery layer over the catalogue metadata

Slide 27: Open Data

Slide 28: There is more to heaven and earth • Licensed content and access • Organization content • The entire biblioverse and Internet

Slide 29: Is there “too much” information?

Slide 30: http://visibleearth.nasa.gov/view_rec.php?id=11793

Slide 31: There is too much information poverty

Slide 32: http://www.flickr.com/photos/w_franklin/51297912/

Slide 33: Seeing the forest - licensed content • Federated search • Local indexing

Slide 34: Seeing the forest - repositories • CARLCore Metadata Application Profile • OAI-PMH • OAI-ORE

Slide 35: I see... everything • XML, RDF, RSS, GeoRSS... • Microformats - Embedded knowledge • Aggregators • Recommender APIs

Slide 36: Glen Newton

Slide 38: Experiment on Humans • CISTI Lab • British Library Labs • National Library of Australia Labs • MIT Libraries Betas • many others...

Slide 39: Free the Humans!

Slide 40: Richard Akerman NRC-CISTI http://www.connotea.org/user/scilib/tag/nisodiscovery2008 © 2008 Government of Canada Licensed in the Creative Commons http://creativecommons.org/licenses/by-nc-sa/2.5/ca/