You want me to do what

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You want me to do what?

• The Transition from Distributed to Unified,
  Federated CombinedSearching
• A somewhat light-hearted view offinding a new
  model for accessto scholarly resources
• Peter Clinton
• Information Technology Services
• June 8, 2005

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Weve come a long way

• We have come a long way since 1989 when we
  introduced our first system for searching
  indexes.
• Today we offer a vast array of electronic
  resources using many systems.
• The expectations of our users have changed as
  well.

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Abstract Index Searching

• Today we offer students and faculty
• 200,000,000 citations
• 500 abstract index titles
• 350 are from 50 systems with multiple databases
• 150 are direct from the vendor
• Over 200 interfaces
• All of them are different!

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You want me to do what?

• Do you expect me to do all that search the
  library stuff? Like, get real! Id rather use
  Google.
• If you were a student today,wouldnt you have
  the samereactions to what we expect?

Fear
Frustration
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Distributed Searching
Many interfaces
Many search engines
Many databases
Many search results
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Unified Searching The Impossible Dream

• Our goal is to provide one place for students and
  faculty to go for all scholarly resources.For
  many reasons this is The Impossible Dreambut
  we are working toward this goal

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Unified Searching
Single interface
Single search engine
Many databases
Single search result
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Unified Searching

• is helping turn these reactions into these

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Unified Searching

• We will never achieve fully unified searching
• No aggregator has everything
• Many database vendors wont allow local loading
• Scholars Portal Search is based on this model
• but it will never have everything
• at best it will have only
• 25 of our titles
• 50 of our citations
• What other will titles will webring into the
  unified model?

Titles
Citations
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What OCUL Holds in Common

• 1,994 subscriptions to A I titles
• gt400 unique titles
• 87 titles held by 7 or more
• 21 from CSA
• 36 titles held by 10 or more
• 12 from CSA
• 25 50 are primecandidates for local loadingas
  OCUL products

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What about the uncommon titles?

• Some OCUL members wish to maximize the potential
  of Scholars Portal Search by incorporating access
  to the uncommon AI databases
• The challenge is how to bring these into the
  Scholars Portal framework while recognizing the
  unique needs of each institution

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What about the uncommon titles?

• OCUL now has an early adopter model that will
  allow us to load UofT titles
• Scholars Portal Search will never have
  everything
• Some publishers wont allow local loading
• Some databases may not be a good fit in terms
  of data structure
• So, what can we do about these

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Federated Searching

• Brings databases into a uniform framework
• Enables the simultaneous searching of many
  resources with a single interface
• What is federated searching?
• A system used to
• execute searches across many different
  information sources
• collect and collate the responses
• present the results in a single list

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Federated Searching

• Can help turn the grumpiest of users from this
  

• to this

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Federated Searching
Search native interface
Single interface Search agent
Many search engines
Many databases
Single search result
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Unified vs Federated Searching
Unified
Federated
Many databases with a unified indexing structure
Many databases each with its own indexing
structure
Database Indexing
There is a single result set for all the
databases
There is a merged result set with the top ?
citations from each database
Search Results
All citations are ranked using the same
algorithm
Ranking is done for each database with the
ranking algorithm of the systems being
searched Undisplayed results from one database
may be more relevant to the query than the
displayed results from another database
Relevancy Ranking



Deduplication of Records

Search Performance
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Unified vs Federated Searching
Database Relevance A Highly B Moderately C
Slightly
Unified
Federated
Many databases with a unified indexing structure
Many different databases each with its own
indexing
Database Indexing
There is a single result set for the database
There is a merged result set with the top ?
citations from each database
Search Results
All citations are ranked using the same
algorithm
Ranking is done for each database with the
ranking algorithm of the systems being
searched Undisplayed results from one database
may be more relevant to the query than the
displayed results from another database
Relevancy Ranking

Deduplication of Records


Search Performance
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Unified vs Federated Searching
Unified
Federated
Many databases with a unified indexing structure
Many different databases each with its own
indexing
Database Indexing
There is a single result set for the database
There is a merged result set with the top ?
citations from each database
Search Results
All citations are ranked using the same
algorithm
Ranking is done for each database with the
ranking algorithm of the systems being
searched Undisplayed results from one database
may be more relevant to the query than the
displayed results from another database
Relevancy Ranking

Because data is managed in a single data
structure with the same database definition, the
masking of duplicate records is reliable
Because data is managed on different systems
with different database definitions, the masking
of dupli-cate records less reliable
Deduplication of Records
Searching is done on a single system on which
performance can be managed
Searching is done on multiple systems on which
performance is managed by each target system
Search Performance
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How Federated Searching Works
Target Database
User enters query
Target system searches database
Search agent sends query to target
Target returns top citations
Search agent collects results
Search agent sends results to user
Search agent merges results
Search agent dedups results
Search agent ranks or orders results
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Federated Search Products

• Product Vendor
  Based on
• AGent Auto-Graphics
• Chameleon VTLS Muse Global
• ERA Endeavor Muse Global
• Horizon Portal Dynix WebFeat
• MetaLib Ex Libris
• MultiSearch CSA Muse Global
• SingleSearch Sirsi Muse Global
• WebFeat 3 WebFeat
• ZPORTAL Fretwell-Downing

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Muse Global

• Muse Metasearch
• provides a single action for simultaneous
  searching across a diverse set of content sources
• gives searchers a single sign-on for
  authenticated access to local and remote
  resources, hiding the complexity of searching
  multiple repositories
• returns results in a consistent, uniform format
  which can then be sorted, filtered and
  de-duplicated
• The Muse Global market is not libraries it is
  information system vendors

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CSA MultiSearch

• We have licensed CSA MultiSearch for use by the
  University of Toronto Libraries
• Brings non-Scholars Portal resources into the
  framework of Scholars Portal Search
• Being considered by other Ontario universities
• Will probably become a Scholars Portal initiative

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CSA MultiSearch

• Provides federated access to resources
• Is powered by the CSA Illumina platform

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Targets Connectors

• Muse Global writes the connectors that link the
  Illumina interface and the target information
  sources
• CSA offers connectors for more than a thousand
  targets
• Targets may be
• Web servers
• Z39.50 servers
• Other information sources

Titles
Citations
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UofT Databases Targets
We must now select our Illumina databases
MultiSearch targets

• Identified targets
• Scopus
• Sirsi
• Library web site
• Process
• To be identified using a Delphi-like method

• Criteria
• Can it be loaded locally?
• Use?
• Size?
• Cost?
• Importance?
• Easeofuse factor?
• Availability of connectors!

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CSA MultiSearch

• CSA will be doing a phased implementation
• Links between applications
• Illumina ? MultiSearch
• Search other databases
• MultiSearch ? Illumina
• Search Scholars Portal databases
• Integration of Illumina MultiSearch
• This will enable Combined Searching

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Combined Searching

• will help our users find their way through the
  maze of resourcesthat we offer
• and will make them happier with searching

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Combined Searching
Search native interface
Single interface Combined search agent search
engine
Unified search Federated search
Many databases
Single search result
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Mixed / Hybrid Searching
50 of our databases 10 of our citations
50 of our databases 90 of our citations
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Features at a glance
The User Perspective
Complexity
Convenience
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Transition Path
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One Size Does Not Fit All

• The federated searching model offers our users
  convenience,
• but as effective this is
• we must recognize that
• it is not a panacea
• it has its limitations
• some users will need native searching

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It is all about the user

• What do we want from our users?
• or
• or do we want

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Questions
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