1. Taxonomy and Knowledge Organization Taxonomy in Context
Tom Reamy Chief Knowledge Architect
KAPS Group
Knowledge Architecture Professional Services

2. Agenda Introduction: Time for Taxonomies
Taxonomy Types: Strengths and Weaknesses
Formal and Browse
Taxonomy in the Organization: Intellectual Infrastructure
Content, People, Activities
Taxonomy Tips and Techniques
Development Stages
Issues and Ideas
Future Directions
Building on the Intellectual Infrastructure

3. KAPS Group Knowledge Architecture Professional Services (KAPS)
Consulting, strategy recommendations
Knowledge architecture audits
Partners – Convera and others
First Convera Certified Taxonomy Developers
Taxonomies: Enterprise, Marketing, Insurance, etc.
Taxonomy customization
Intellectual infrastructure for organizations
Knowledge organization, technology, people and processes
Search, content management, portals, collaboration, knowledge management, e-learning, etc.

4. Time for Taxonomies Taxonomy Time: Technology is not delivering
Professionals spend more time looking for information than using it
50% of them spend > 2 hours a day looking
Search not enough – text strings vs. concepts
Relevance isn’t very relevant
Data mining misses 80% of significant content
Text mining needs more structure (taxonomies)
Surveys
76% say taxonomies are important
90% plan on a taxonomy strategy in 24 months

5. Time for Taxonomies: Word of Caution
Taxonomy is not the answer
Is this a taxonomy?
Inventories, catalogs, classifications, categorization schemas, thesauri, controlled vocabularies
Taxonomy not enough – need other structures
Metadata, facets
Taxonomies have to be used to be useful
How to fail:
Taxonomy as a project
Taxonomy as a search engine project afterthought

6. Two Types of Taxonomies: Browse and Formal Browse Taxonomy – Yahoo

7. Browse Taxonomies: Strengths and Weaknesses
Strengths: Browse is better than search
Context and discovery
Browse by task, type, etc.
Weaknesses:
Mix of organization
Catalogs, alphabetical listings, inventories
Subject matter, functional, publisher, document type
Vocabulary and nomenclature Issues
Problems with maintenance, new material
Poor granularity and little relationship between parts.
Web site unit of organization
No foundation for standards

8. Formal Taxonomies: Strengths and Weaknesses
Fixed Resource – little or no maintenance
Communication Platform – share ideas, standards
Infrastructure Resource
Controlled vocabulary and keywords
More depth, finer granularity
Weaknesses:
Difficult to develop and customize
Don’t reflect users’ perspectives
Users have to adapt to language

9. Dynamic Classification: Best of Both Worlds
Search and browse better than either alone
Categorized search – context
Browse as an advanced search
Dynamic search and browse is best
Can’t predict all the ways people think
Advanced cognitive differences
Panda, Monkey, Banana
Can’t predict all the questions and activities
Intersections of what users are looking for and what documents are often about
China and Biotech
Economics and Regulatory
Facet Taxonomies
Actors, events, functions, geography

10. Taxonomy in Context: Intellectual Infrastructure
3 infrastructures: technology, organizational, intellectual
Technology – systems and applications, servers and desktops, programmers and help desks, etc.
Organizational – business units and project groups, policies and procedures, administrators and facilitators
Intellectual – Information and knowledge, vocabularies and applications, authors and editors and librarians
Taxonomy at the nexus of the three infrastructures
Taxonomy enables communication among people, content, and technology

11. Taxonomy in the Organization: Project Approach or Infrastructure Approach
Situation: Problem with access to information
Project Approach
Publish everything on the intranet
Buy a search engine
Do some keyword and usability tests
Buy a portal (or two)
Buy content management software
Try knowledge organization – taxonomy?
Infrastructure Approach
“The path up and down is one and the same.” (Heraclitus)

12. Taxonomy in the Organization: Why an Infrastructure Approach?
Immanuel Kant
“Concepts without percepts are empty.”
“Percepts without concepts are blind.”
Knowledge Management (KM) / Information Projects
KM without applications is empty
Strategy only, management fad
Elegant taxonomies – unused
Applications without knowledge architecture (KA) are blind
IT based KM
Fragmented applications

13. Taxonomy in the Organization: Structuring Content
All kinds of content
Structured and unstructured, Internet and desktop
Metadata standards – Dublin core+
Keywords - poor performance
Need controlled vocabulary, taxonomies, semantic network
Document Type
Form, policy, how-to, etc.
Dynamic classification with subject matter taxonomies
Audience
Role, function, expertise, information behaviors
Consistent across subject matter and people
Best bets metadata

14. Taxonomy in the Organization: Structuring People
Individual People
Tacit knowledge, information behaviors
Advanced personalization – category priority
Sales – forms ---- New Account Form
Accountant ---- New Accounts ---- Forms
Communities
Variety of types – map of formal and informal
Variety of subject matter – vaccines, research, scuba
Variety of communication channels and information behaviors
Community-specific vocabularies, need for inter-community communication (Cortical organization model)

15. Taxonomy in the Organization: Structuring Processes and Technology
Technology: infrastructure and applications
Enterprise platforms: from creation to retrieval to application
Taxonomy as the computer network
Applications – integrated meaning, not just data
Creation – content management, innovation, communities of practice (CoPs)
When, who, how, and how much structure to add
Workflow with meaning, distributed subject matter experts (SMEs) and centralized teams
Retrieval – standalone and embedded in applications and business processes
Portals, collaboration, text mining, business intelligence, CRM

16. Taxonomy in the Organization: The Integrating Infrastructure
Starting point: knowledge architecture audit, K-Map
Social network analysis, information behaviors
People – knowledge architecture team
Infrastructure activities – taxonomies, analytics, best bets
Facilitation – knowledge transfer, partner with SMEs
“Taxonomies” of content, people, and activities
Dynamic Dimension – complexity not chaos
Analytics based on concepts, information behaviors
Taxonomy is the answer
In an Infrastructure Context

17. Taxonomy Development: Tips and Techniques Stage One – How to Begin
Step One: Strategic Questions – why, what value from the taxonomy, how are you going to use it
Variety of taxonomies – important to know the differences, when to use what.
Step Two: Get a good taxonomist! (or learn)
Library Science+ Cognitive Science + Cognitive Anthropology
Step Three: Software Shopping
Automatic Software – Fun Diversion for a rainy day
Uneven hierarchy, strange node names, weird clusters
Taxonomy Management, Entity Extraction, Visualization
Step Four: Get a good taxonomy!
Glossary, Index, Pull from multiple sources
Get a good document collection

18. Combination of top down and bottom up (and Essences)
Taxonomy Development: Tips and Techniques Stage Two: Development and/or Customization
Combination of top down and bottom up (and Essences)
Top: Design an ontology, facet selection
Bottom: Vocabulary extraction – documents, search logs, interview authors and users
Develop essential examples (Prototypes)
Most Intuitive Level – genus (oak, maple, rabbit)
Quintessential Chair – all the essential characteristics, no more
Work toward the prototype and out and up and down
Repeat until dizzy or done

19. Taxonomy Development: Tips and Techniques Stage Three: Evaluate and Refine
Formal Evaluation
Quality of corpus – size, homogeneity, representative
Breadth of coverage – main ideas, outlier ideas (see next)
Structure – balance of depth and width
Kill the verbs
Evaluate speciation steps – understandable and systematic
Person – Unwelcome person – Unpleasant person - Selfish person
Avoid binary levels, duplication of contrasts
Primary and secondary education, public and private

20. Taxonomy Development: Tips and Techniques Stage Three: Evaluate and Refine
Practical Evaluation
Test in real life application
Select representative users and documents
Test node labels with Subject Matter Experts
Balance of making sense and jargon
Test with representative key concepts
Test for un-representative strange little concepts that only mean something to a few people but the people and ideas are key and are normally impossible to find

21. Taxonomy Development: Tips and Techniques Issues and Ideas
Complex Topics – intersection of subject domains and facets
What documents are often about is the intersection
Example – China and Biotech
Standards and Customization
Balance of corporate communication and departmental specifics
At what level are differences represented?
Customize pre-defined taxonomy – additional structure, add synonyms and acronyms and vocabulary

22. Taxonomy Development: Tips and Techniques Issues and Ideas
Enterprise Taxonomy
No single subject matter taxonomy
Need an ontology of facets or domains
Enterprise Facet Model:
Actors, Events, Functions, Locations, Objects, Information Resources
Combine and map to subject domains

23. Future Directions: Knowledge Organization
New analytic methods
Cognitive anthropology, history of ideas, ESNA
New metadata schemas
SCORM, RDF and semantic Web
Learning and knowledge objects
New people models
Bloom’s Taxonomy, Gardner’s 7 Intelligences
Advanced personalization
Community-based, cognitive-based
Adaptive, dynamic presentation variations

24. Future Directions: Technology
Taxonomies within applications
Richer world knowledge and better learning
Entity extraction and fact extraction
Natural language processing (NLP) search – answers, not document lists
Integrated KM platform
Creation, structure, retrieval, application, measurement
Integrated KM/KA team
Contextualizing content: related content, best bets, expertise, communities

25. Future Directions: Well-Articulated Organization
Learning takes place throughout the system
Smart applications – adapts to users’ and community’s activities
Just-in-time training and performance support
Combination of analytics and knowledge organization
Concept-level, not document-level
Taxonomy is the brain, analytics are the eyes
Self-knowledge – highest form of knowledge
“Unexamined life is not worth living.” (Plato)
Unexamined, inarticulate enterprise is not worth having

26. The Contextual Desktop: Document, List of Documents, Applications Screen
Before you view:
Agent keeps you up to date
Your connections to content and communities, your preferences
Your history and the history of other members of your communities
When you add/change content
Suggests categorization value, metadata values
Routes to appropriate content and communities
Prompt on unusual connections
Pre-existing content
Related content
Regulatory issues
Ask the question – route to experts?
When you look for information
Taxonomy-based dynamic browse
Entities
People, companies, wells
Related content
Regulatory, patents, BI-CI
Geological data
News stories
Dictionaries, USGS data, databases
Experts
Ask questions, chat
When you use information
Communities
Search, chat,
Performance aids, classes
Stories

27. Sources Books Software Courses Women, Fire, and Dangerous Things
What Categories Reveal about the Mind
Geroge Lakoff
The Geography of Thought
Richard E. Nisbett
Software
Convera Retrievalware
Inxight Smart Discovery – entity and fact extraction
Courses
Convera Taxonomy Certification

28. Questions? Tom Reamy tomr@kapsgroup.com KAPS Group
Knowledge Architecture Professional Services