20th Oct 2008Colin Bird, © 2008 IBM Corporation 1 Seek and ye might find The universe is finite … or is it?

20th Oct 2008 Colin Bird, © 2008 IBM Corporation 1

Seek and ye might find

The universe is finite … or is it?

Colin Bird, © 2008 IBM Corporation 220th Oct 2008

Why this talk?

e-Research

course

Extreme Blue

Retrievability issue

Ideas


Retrievability in context

A Big issue IBM customers Google but …

Information availability Cliché Presumption of need


The endless cycle of idea and action, Endless invention, endless experiment, ... All our knowledge brings us nearer to our ignorance ... Where is the wisdom we have lost in knowledge? Where is the knowledge we have lost in information?

T. S. Eliot – The Rock (1934)


Product information

Concepts

Understanding

(?)

Primarily task-based

IEHS


Retrieval with IEHS

Navigation

Search [Help System]

Links


Search and ye shall find …… or shall ye?

The hits contain the search terms, but are not necessarily about them.

RelevantDocuments

HitsRelevant Hits

Recall = RH / RD Precision = RH / H Minimise H-RH

Also important: a manageable number of hits!


Improving retrieval with IEHS

Facet browsing

Classified with a taxonomy


Principles of faceted classification

Categories: Fundamental to the

domain Often class hierarchies Almost always

mutually exclusive

Intersections SWED … Still TMI? Why do we classify

things?What are we hoping for?


Why do we …?

organise things

put things into

categories

look for patterns

arrange things to fit our models


“Classification, broadly defined, is the act of organising the universe of knowledge into some systematic order. It has been considered the most fundamental activity of the human mind.”

Lois Mai Chan (Library Science expert)

“People naturally group things into classes … By dealing with classes rather than individual things, we can organize our knowledge of the world in a concise and practical way. Faced with an escaped Rhinoceros, it's helpful to quickly

think, ‘Dangerous wild animal - take cover’. “

Paul Englefield (IBM colleague)


We classify …

To make information and knowledge:Easier to findQuicker to find

To model understandingLinnaeus – classification of speciesSynonyms

Characterize Categorize


Scientists …

“Scientific method depends upon increasingly more sophisticated characterizations of subjects of the investigation.” [Wikipedia]

Organise Explain Predict Experiment



Making information easier to find

Narrow the browsing space: Use metadata to describe what information is about Exploit the metadata that others have provided

Classification can at least help to structure the information universe into manageable chunks.

Astronomers say the universe is finite, which is a comforting thought for those people who

can't remember where they leave things.

Woody Allen


Two forms of narrowing

Labelling: the system identifies the items that are about the subjects users are interested in

Filtering: the system withholds information that isdeemed to be not relevant

Can employ both

Labelled: relevant

Filtered to omit content that is

not relevant


Labelling: Classification vs Indexing

A isAbout X Group similar items Offer items for selection

B isRelevantTo Y Distinguish similar items Facilitate rapid access to

a specific item of interest

Compare?

Contrast?

Scope of control

Indexing

Classification


For classification to be effective,

We need the right: Categories Subjects Devices for capturing

the metadata


Where do categories come from?

---------------

--------------------

---------------

----------

----------

----------

----------

----------

structure

How? Nature

orNurture?

Nature : self-organising? or

Nurture : invented and imposed?


Dewey Decimal Classification: 200: Religion210 Natural theology

220 Bible

230 Christian theology

240 Christian moral & devotional theology

250 Christian orders & local church

260 Christian social theology

270 Christian church history

280 Christian sects & denominations

290 Other religions

Is this what you want in the 21st Century?Adapted from Clay Shirky’s Writings


Organising classification metadata

Controlled vocabulary Consistent Unambiguous

Structure Levels of detail Exploit relationships

Options: Term list Taxonomy Ontology Folksonomy – how does this fit in?


Information systems context:A classification of concepts into a hierarchical

structure according to whether the concepts are more general or more specific

A biological definition: “A classification of living organisms into a

hierarchical structure of species, genera, families etc.”

Taxonomy


Folksonomy [Social tagging]

Familiar representation End-user participation Share descriptions

Related terms (not synonyms) Process vs Outcome Vocabulary space

Collaborative tagging Knowledge organisation and discovery Community control


Vocabulary control - for and against

Context: delivering online informationDeclaration of coverageRetrieval of topics about a subject

Precision vs Recall Rigid structures vs Flexibility

Classification Community organising Content-based search


Information classification in IBM context

Information centers (IEHS) and ibm.com Taxonomy structure

Vocabulary control (across IBM)Extension modelGovernance process

…… is this enough?


Towards an alliance Both seek to enhance retrievability Taxonomies provide a consistent and unambiguous

structure. Folksonomies involve real users, are initially uncontrolled,

but the community exerts control over time One regrettable and overly pessimistic distinction:

Classification imposes structure (and so freezes content)

Static

Community organising encourages end-user input

Dynamic


Basis for an Extreme Blue

project

Taxonomy IEHS

Facet browser

Collaborative taggingFolksonomy

Added value:• retrieval

• user insights

Retrievability issue


Some alliance issues Points of difference:

Consistency & Ambiguity Control Imposed structures versus end-user input

Usability, in a wide sense of the term Scalability, particularly if number of terms in the folksonomy

exceeds significantly the number of subjects in the taxonomy Does the approach scale to communities larger than a group of like-

minded individuals? What life-cycle model is appropriate for folksonomy-type metadata? Relationships between social tagging and facet browsing, and other

forms of information filtering, considering also the governance of those relationships.

Reliability of user tagging behaviour indicators when considering the information structure and architecture.


Enhanced Tagging for Discovery (EnTag) "combination and comparison of controlled and

folksonomy approaches" "attempting to get the best of both worlds“

TAXONOMY DIRECTED FOLKSONOMIES Integrating user tagging and controlled vocabularies

for Australian education networks

“How Semantic Tagging Increases Findability”http://www.hedden-information.com/

articles.htm

Not alone …


The Extreme Blue Programme

Premiere IBM Summer Vacation Scheme Brightest & best students! Real IBM incubator projects

Team based projects Business & technical students Mentors

12 Weeks, June – September Culminates in EMEA Expo Worldwide…


Extreme Blue Worldwide…

Austin

San Jose

Raleigh

Dublin

Hursley

La Gaude

Amsterdam

Böblingen

Beijing

Bangalore

Toronto

Brazil


Why Extreme Blue?

Projects

Patents

People

Media

TalentInnovation Proofs of concepts

Works for IBM Could work for anyone Requires commitment


sTAGr

Maybe a few words about the origin of the name …


What did sTAGr aim to do?

Formal and informal – both options Insights from tags used and topics tagged Dynamic vocabularies – explore issues

Individuals and groups have a significantly better prospect of locating the information they need if they contribute to the

classification and organisation of the

information


sTAGr = social tagging in IEHS Technical stuff

Back-end server to store the folksonomyTagging interfaces and “tag analysis” Investigate the potential issues

Usability testing Business student:

Internal marketingWhitepaper


Tagging UI locations


Links to Tag Clouds

Sections Minimise

Help Page

Visible Ratings See All Tags on

Topic

Tag UI


Project Findings

100%

Faster100%

Faster


Résumé

Adding a tagging facility does improve retrievability, but …

Original justification included the phrase:“smarter and more responsive routes to information discovery”

Can the alliance of a folksonomy and a formal taxonomy further enhance retrievability?


Tag “analysis”

Similarly-tagged topics and similar tags Synonyms Homographs

Structure from tag sets

Problems: Unstable folksonomy Autotagger distortion


Dynamic vocabularie

s

Combined interface

Informing the taxonomy

Informing the information architecture

How about the original ideas …


In the crystal ball …

Potential developments from sTAGr:

1. Adaptive browsing, using facet browser interfaces that users personalise by combining their own tags with the subject entry points provided by the formal taxonomy

2. Dynamic vocabularies that present users with a merger of formal and informal classification terms, generated dynamically each time a given user accesses the information center

3. Batch analysis of user tagging behaviour to generate recommendations about information restructuring and subject coverage, thereby enabling the information itself to evolve according to user practice

4. … and a new name


Choice:Combined interface

DynamicvocabularyConsistent

Unambiguous

User inputRelevance

Personalize

or

Exploit other users’ tags

Find entry point

Facet browser


Informing the taxonomy

Controlled vocabulary, slow to changeUnambiguous definition, maybe scope noteMOAT - http://moat-project.org/

Populating facetsExtension taxonomiesSparse classification: entry pointsTags become candidate subjectsTag rating: collaborative selection


Tag “analysis” revisited Informing the taxonomy

Eliciting emergent structure within the folksonomy Identifying potential synonyms and homographs Discovering relationships between tags and subjects

in the taxonomy, exploiting the topic structure to do so Informing the information architecture

Analysing user tagging behaviour to generate recommendations about the structure of the information space

Analysing user tagging behaviour to generate recommendations about the coverage of the taxonomy and the relevance of some terms within it


Acknowledgements

Timothy Catt Tom Clabon David Rankine James Thompson

Cerys Giddings Scott Couper1

Loughborough University

University of Bristol

University of St. Andrews

University of York

IBM Technical mentor

IBM Business mentor


?