information retrieval in libraries: silos and (tentative) solutions daniel hickey 15 sept 2010
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Information Retrieval in Libraries: Silos and (Tentative) Solutions
Daniel Hickey15 Sept 2010
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IR of Academic Information1990• Print and electronic indexes• Libraries!
2010• Networked databases• Libraries?
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User-Centered PerspectiveKnowing which databases to use: We offer hundreds of different databases and tens of thousands of different ejournals. Does the user know which of these are the best for their research?
Duplication of effort:Even if the user knows which database to search, she still has to perform the same search in every database that's relevant to her topic.
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500+ Databases with…• Vastly different content• Vendor-side legacy systems• Competing metadata standards• License agreements and copyright restrictions
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THE ECONOMIST
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Libraries are trying to meet the needs of 21st Century researchers with late 20th Century technology.
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What’s at stake?
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• Attrition and research integrity• Interdisciplinary research• Discoverability of– Data– Multimedia– Grey literature
What’s at Stake?
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(Elephant in the room)
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• Attrition and research integrity• Interdisciplinary research• Discoverability of– Data– Multimedia– Grey literature
What’s at Stake?
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• Attrition and research integrity• Interdisciplinary research• Discoverability of– Data– Multimedia– Grey literature
What’s at Stake?
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Solutions: First Attempts• Database directories• Federated search• Link resolvers• Metadata standards
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Directories
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Solutions: First Attempts• Database directories• Federated search• Link resolvers• Metadata standards
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Link Resolvers
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Solutions: First Attempts• Database directories• Federated search• Link resolvers• Metadata standards
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Solutions: 2010• Deep index
• Big Digital Machine
• Linked data
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Deep Index: Summon
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Summon Pitfalls• Prohibitively expensive• Not designed with new
needs in mind:– Datasets– Multimedia
• Vendor-controlled / SaaS
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The Big Digital Machine “aims to provide for the production, distribution, management, and preservation of the full range of scholarly products[…] To date there have been a number of good systems developed to do parts of this work, but these developments are separate, small-scale and not integrated.”
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Or…
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Big Digital MachinePro:• Apply successful model to
new “product”• Take control of academic
output / address the serials crisis directly
• Provide the elusive single entry point
Con:• Untested business model• Import of current publishing
system:– Industry– Peer Review / P&T
• Deus ex machina
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Linked Data• Method “of exposing, sharing, and connecting
data via dereferenceable URIs on the Web”• Conceptual offshoot of the Semantic Web• Effectively untested in the academic
publishing environment
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Linked DataTim Berners-Lee:
1. Use URIs as names for things2. Use HTTP URIs so that people can look up those names3. When someone looks up a URI, provide useful
information, using the standards (RDF/XML, SPARQL)4. Include links to other URIs so that they can discover more
things