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Open Web and Social Frameworks: 
       The Libraries’ New Frontier to 
    Accomplish Their Social and Cultural 
                  Mission

 Zheng (John) Wang              Kevin Rundblad
 Head, Web Services        UX and Social Tech Strategist
    UCLA Library                  UCLA Library
Library Social and Culture Functions
"Separately a book stock and a catalog would 
be comparatively weak, but together they 
possess a unique cultural potency."
‐ Pierce Bulter, Cultural Function of the Library, 1952
True for paper and print 
        paradigm
False for the Internet Age
Library Functions are Challenged
HTML brought content and their metadata 
together onto one web page
Digital medium dictates how users consume content


Therefore HTML possesses a stronger cultural 
potency than OPAC and its book stocks.
User Expectation



Immediate, efficient, and convenient access to 
information
Library Practices

Metadata is an means to an end

Libraries offers metadata search (OPAC) as a 
destination on the web
“… publications that are not instantly 
available in full‐text will become kind of 
second‐rate in a sense… become much less 
visible to the reader community.”
‐ Clifford Lynch, 1997
Library Content Workflow Model
Manual metadata creation to 
describe its collections
Resources intensive   Time Consuming   Back Logs
Metadata creation speed is slower than 
content publishing rate
Call for a New Library Model
for processing and sharing collections in the Digital Age
Case Study: iCon (iContribute)
Fast content workflow process, web publishing, and social curation 
platform
iCon Key Functionalities
1. Automate collection process as much as possible
   Digital Camera, OCR, indexing engine, and semantic web technologies 
   replacing manual cataloging and metadata creation process
iCon Key Functionalities
1. Automate collection process as much as possible
   Digital Camera, OCR, indexing engine, and semantic web technologies 
   replacing manual cataloging and metadata creation process


2. Social Framework
   Collaborate between libraries and among users to fine tune metadata 
   and create new content to aid better discovery experience 
iCon as AI

Automating Collection Processing
OCR 
                                   process on 
                        Direct       server
                       Upload                    Text/Images 
                        from                       stored in 
                       camera                     database




     Digital 
    Imaging
                                  iCon                              Searchable 
                                                                    full text of 
                                                                      pages 



Using digital camera                                               With images
                                                                And abstracted text
iCon Processing Rate
                            Process Rate
                       (Records/Hour/Person)




Original Cataloging             2




Copy Cataloging                 6




iCon                            12




                                 Conservative Estimate
iCon Processing Rate
                            Process Rate           Monthly Total
                       (Records/Hour/Person)   (160 Working Hours/Person)




Original Cataloging             2                        320




Copy Cataloging                 6                        960




iCon                            12                      1920




                                 Conservative Estimate
iCon Processing Rate
                            Process Rate           Monthly Total                  Yearly Total
                       (Records/Hour/Person)   (160 Working Hours/Person)   (1920 Working Hours/Person)




Original Cataloging             2                        320                          3840




Copy Cataloging                 6                        960                         11520




iCon                            12                      1920                         23040




                                 Conservative Estimate
iCon Economics
                           Process Rate            Labor Cost
                                                                     Per Record Cost
                      (Records/Hour/Person)   (Dollar/hour/Person)




Original Cataloging            2                                         $12.50


                                                     $25.00


Copy Cataloging                6                                          $4.16




iCon                           12                    $10.00               $0.83




                                Conservative Estimate
iCon as Social Framework


 Human Computation / Crowdsourcing
Human Computation 
Human processing for solving computational 
Tasks that are considered difficult for AI, but 
nominal for humans.
Crowdsourcing
Leveraging a community/group to collectively
produce a desired task.
Examples of Crowdsourcing
Wikipedia                                    (social knowledge)
Youtube                                      (entertainment)
Yelp                                         (social sentiment/ratings)
StackOverflow                                (community knowledge)
Australian Newspaper Digitisation Program    (Human Computation)
Is the Crowd Credible?
Australian Newspaper 
 Digitisation Program 
   National Library of Australia
12.5 million lines of text corrected 
    by the public in 17 months
Crowdsourcing… 
...handles difficult AI tasks, but nominal for human

…provides local knowledge input

…is perspectival in nature
Crowdsourcing = Unique Knowledge 
Expertise is spread across
   many individuals…
…Rather than focused
   in one expert.
Crowdsourcing creates
favorable probabilities
for knowledge creation
Social Knowledge 
is Local Knowledge
Social Knowledge 
is Perspectival in Nature
How can Libraries leverage
      the crowd?
Create Open Library Catalogs
 to enable social knowledge
Social Framework Example:

The Wiki‐fication of Online
    Catalog Records
User Generated Content (UGC)
User Generated Content (UGC)




 Book Summaries/Description
User Generated Content (UGC)




 User Ratings
User Generated Content (UGC)




 User Reviews
User Generated Content (UGC)




 Quotes from Item
User Generated Content (UGC)




 User Tags
User Generated Content (UGC)




 Related Links: Author/Subject based
 articles, slides, video, etc…
User Generated Content (UGC)




 The record becomes the container for 
 aggregating social content…
User Generated Content (UGC)




 …and user decision point for
 the value of content.
What are the implications
of the Wiki Book Record?
User Decision making is enhanced
       at the record level
User participation
builds efficient metadata
   and partial content
Real‐time information
sources are created from 
 User Generated Content
Real‐time information
sources are created from 
 User Generated Content

Searching UGC leads to discovering
Content via new channels
People like to do/see what
   others are doing…

 Concept: “Social Proof”
All UGC From book records
is output in real‐time feed
Think of it as a Twitter
for your Online Catalog
iCon Architecture
iCon Architecture
1. Open Data
  Programmable by 3 party users
iCon Architecture
1.   Open Data
     Programmable


2. Open Process
     Crowdsourcing for processing collections and enrich collections
iCon Architecture
1.   Open Data
     Programmable
2.   Open Process
     Crowdsourcing , User  Curation

3. Open Platform
     PaaS and SaaS: allow users to freely add content and provide 
     users with mashup services
iCon Architecture
1.   Open Data
     Programmable
2.   Open Process
     Crowdsourcing , User  Curation
3.   Open Platform
     PaaS and SaaS: allow users to freely add content and provide users with mashup 
     services


4. Open Standards
     HTML based for scalability
iCon Architecture
1.   Open Data
     Programmable
2.   Open Process
     Crowdsourcing , User  Curation
3.   Open Platform
     PaaS and SaaS: allow users to freely add content and provide users with mashup 
     services

4.   Open Standards
     HTML based for scalability

5. Open Source Where Possible
     use open source software to keep the cost down
Open Web = Library Values
• Libraries promote free information sharing
• Libraries are places for remixing and 
  recreating content

  Open Web rejuvenates libraries to continue  
  social and culture functions in the Internet 
  Age.
Questions



    Zheng (John) Wang               Kevin Rundblad
    Head, Web Services         UX and Social Tech Strategist
 Co‐Manager Simul8 Group        Co‐Manager Simul8 Group
       UCLA Library                   UCLA Library
zhengwang@library.ucla.edu   kevinrundblad@library.ucla.edu

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Open Web and Social Frameworks for Libraries