1. Taxonomy Development An Infrastructure Model
Tom Reamy Chief Knowledge Architect
KAPS Group
Knowledge Architecture Professional Services

2. Agenda Introduction Type of Taxonomies The Enterprise Context
Making the Business Case
Infrastructure Model of Taxonomy Development
Taxonomy in 4 Contexts
Content, People, Processes, Technology
Infrastructure Solutions – the Elements
Applying the Model – Practical Dimension
Starting and Resources
Conclusion

3. KAPS Group Knowledge Architecture Professional Services (KAPS)
Consulting, strategy recommendations
Knowledge architecture audits
Partners – Convera, Inxight, FAST, and others
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. Two Types of Taxonomies: Browse and Formal Browse Taxonomy – Yahoo

5. Two Types of Taxonomies: Formal

6. 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

7. 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

8. Facets and Dynamic Classification
Facets are not categories
Entities or concepts belong to a category
Entities have facets
Facets are metadata - properties or attributes
Entities or concepts fit into one category
All entities have all facets – defined by set of values
Facets are orthogonal – mutually exclusive – dimensions
An event is not a person is not a document is not a place.
Facets – variety – of units, of structure
Date or price – numerical range
Location – big to small (partonomy)
Winery – alphabetical
Hierarchical - taxonomic

9. Faceted Navigation: Strengths and Weaknesses
More intuitive – easy to guess what is behind each door
20 questions – we know and use
Dynamic selection of categories
Allow multiple perspectives
Trick Users into “using” Advanced Search
wine where color = red, price = x-y, etc..
Weaknesses:
Difficulty of expressing complex relationships
Simplicity of internal organization
Loss of Browse Context
Difficult to grasp scope and relationships
Limited Domain Applicability – type and size
Entities not concepts, documents, web sites

10. Dynamic Classification / Faceted navigation
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

11. Business Case for Taxonomies: The Right Context
Traditional Metrics
Time Savings – 22 minutes per user per day = $1Mil a Year
Apply to your organization – customer service, content creation, knowledge industry
Cost of not-finding = re-creating content
Research
Advantages of Browsing – Marti Hearst, Chen and Dumais
Nielsen – “Poor classification costs a 10,000 user organization $10M each year – about $1,000 per employee.”
Stories
Pain points, success and failure – in your corporate language

12. Business Case for Taxonomies: IDC White Paper
Information Tasks
– 14.5 hours a week
Create documents – 13.3 hours a week
Search – 9.5 hours a week
Gather information for documents – 8.3 hours a week
Find and organize documents – 6.8 hours a week
Gartner: “Business spend an estimated $750 Billion annually seeking information necessary to do their job % of a knowledge worker’s time is spent managing documents.”

13. Business Case for Taxonomies: IDC White Paper
Time Wasted
Reformat information - $5.7 million per 1,000 per year (400M)
Not finding information - $5.3 million per 1,000 (370M)
Recreating content - $4.5 Million per 1,000 (315M)
Small Percent Gain = large savings
1% - $10 million
5% - $50 million
10% - $100 million

14. Business Case for Taxonomies: The Right Context
Justification
Search Engine - $500K-$2Mil
Content Management - $500K-$2Mil
Portal - $500-$2Mil
Plus maintenance and employee costs
Taxonomy
Small comparative cost
Needed to get full value from all the above
ROI – asking the wrong question
What is ROI for having an HR department?
What is ROI for organizing your company?

15. Ideas – Content Structure
Infrastructure Model of Taxonomy Development Taxonomy in Basic 4 Contexts
Ideas – Content Structure
Language and Mind of your organization
Applications - exchange meaning, not data
People – Company Structure
Communities, Users, Central Team
Activities – Business processes and procedures
Central team - establish standards, facilitate
Technology / Things
CMS, Search, portals, taxonomy tools
Applications – BI, CI, Text Mining

16. Taxonomy in Context Structuring Content
All kinds of content and Content Structures
Structured and unstructured, Internet and desktop
Metadata standards – Dublin core+
Keywords - poor performance
Need controlled vocabulary, taxonomies, semantic network
Other Metadata
Document Type
Form, policy, how-to, etc.
Audience
Role, function, expertise, information behaviors
Best bets metadata
Facets – entities and ideas
Wine.com

17. Taxonomy in Context: 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)

18. Taxonomy in Context: 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

19. Taxonomy in Context: 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 as part of a foundation, not a project
In an Infrastructure Context

20. Taxonomy in Context: The Integrating Infrastructure
Integrated Enterprise requires both an infrastructure team and distributed expertise.
Software and SME’s is not the answer - keywords
Taxonomies not stand alone
Metadata, controlled vocabularies, synonyms, etc.
Variety of taxonomies, plus categorization, classification, etc.
Important to know the differences, when to use which
Multiple Applications
Search, browse, content management, portals, BI & CI, etc.
Infrastructure as Operating System
Word vs. Word Perfect
Instead of sharing clipboard, share information and knowledge.

21. Knowledge Map - Understand what you have, what you are, what you want
Infrastructure Solutions: The start and foundation Knowledge Architecture Audit
Knowledge Map - Understand what you have, what you are, what you want
The foundation of the foundation
Contextual interviews, content analysis, surveys, focus groups, ethnographic studies
Category modeling – “Intertwingledness” -learning new categories influenced by other, related categories
Natural level categories mapped to communities, activities
Novice prefer higher levels
Balance of informative and distinctiveness
Living, breathing, evolving foundation is the goal

22. Knowledge Architect and learning object designers
Infrastructure Solutions: Resources People and Processes: Roles and Functions
Knowledge Architect and learning object designers
Knowledge engineers and cognitive anthropologists
Knowledge facilitators and trainers and librarians
Part Time
Librarians and information architects
Corporate communication editors and writers
Partners
IT, web developers, applications programmers
Business analysts and project managers

23. Infrastructure Solutions: Resources People and Processes: Central Team
Central Team supported by software and offering services
Creating, acquiring, evaluating taxonomies, metadata standards, vocabularies
Input into technology decisions and design – content management, portals, search
Socializing the benefits of metadata, creating a content culture
Evaluating metadata quality, facilitating author metadata
Analyzing the results of using metadata, how communities are using
Research metadata theory, user centric metadata
Design content value structure – more nuanced than good / poor content.

24. Infrastructure Solutions: Resources People and Processes: Facilitating Knowledge Transfer
Need for Facilitators
Amazon hiring humans to refine recommendations
Google – humans answering queries
Facilitate projects, KM project teams
Facilitate knowledge capture in meetings, best practices
Answering online questions, facilitating online discussions, networking within a community
Design and run KM forums, education and innovation fairs
Work with content experts to develop training, incorporate intelligence into applications
Support innovation, knowledge creation in communities

25. KM/KA Dept. – Cross Organizational, Interdisciplinary
Infrastructure Solutions: Resources People and Processes: Location of Team
KM/KA Dept. – Cross Organizational, Interdisciplinary
Balance of dedicated and virtual, partners
Library, Training, IT, HR, Corporate Communication
Balance of central and distributed
Industry variation
Pharmaceutical – dedicated department, major place in the organization
Insurance – Small central group with partners
Beans – a librarian and part time functions
Which design – knowledge architecture audit

26. Infrastructure Solutions: Resources Technology
Taxonomy Management
Text and Visualization
Entity and Fact Extraction
Text Mining
Search for professionals
Different needs, different interfaces
Integration Platform technology
Enterprise Content Management

27. 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

28. Infrastructure Solutions: Taxonomy Development Stage Two: Taxonomy Model
Enterprise Taxonomy
No single subject matter taxonomy
Need an ontology of facets or domains
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
Enterprise Facet Model:
Actors, Events, Functions, Locations, Objects, Information Resources
Combine and map to subject domains

29. Combination of top down and bottom up (and Essences)
Taxonomy Development: Tips and Techniques Stage Three: 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
Map the taxonomy to communities and activities
Category differences
Vocabulary differences

30. Taxonomy Development: Tips and Techniques Stage Four: 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

31. Taxonomy Development: Tips and Techniques Stage Four: 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

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

33. Conclusion Taxonomy development is not just a project
It has no beginning and no end
Taxonomy development is not an end in itself
It enables the accomplishment of many ends
Taxonomy development is not just about search or browse
It is about language, cognition, and applied intelligence
Strategic Vision (articulated by K Map) is important
Even for your under the radar vocabulary project
Paying attention to theory is practical
So is adapting your language to business speak

34. Conclusion Taxonomies are part of your intellectual infrastructure
Roads, transportation systems not cars or types of cars
Taxonomies are part of creating smart organizations
Self aware, capable of learning and evolving
Think Big, Start Small, Scale Fast
If we really are in a knowledge economy
We need to pay attention to –
Knowledge!

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