Taxonomy and Knowledge
Organization
Taxonomy in Context
Tom Reamy
Chief Knowledge Architect
KAPS Group
Knowledge Architecture Professional Services
http://www.kapsgroup.com
Agenda
 Introduction: Time for Taxonomies
 Taxonomy Types: Strengths and Weaknesses
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Formal and Browse
 Taxonomy in the Organization: Intellectual Infrastructure
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Content, People, Activities
 Taxonomy Tips and Techniques
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Development Stages
– Issues and Ideas
 Future Directions
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Building on the Intellectual Infrastructure
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KAPS Group
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Knowledge Architecture Professional Services (KAPS)
Consulting, strategy recommendations
Knowledge architecture audits
Partners – Convera and others
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First Convera Certified Taxonomy Developers
 Taxonomies: Enterprise, Marketing, Insurance, etc.
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Taxonomy customization
 Intellectual infrastructure for organizations
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Knowledge organization, technology, people and processes
Search, content management, portals, collaboration,
knowledge management, e-learning, etc.
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Time for Taxonomies
 Taxonomy Time: Technology is not delivering
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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
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Relevance isn’t very relevant
 Data mining misses 80% of significant content
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Text mining needs more structure (taxonomies)
 Surveys
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76% say taxonomies are important
90% plan on a taxonomy strategy in 24 months
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Time for Taxonomies: Word of Caution
 Taxonomy is not the answer
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Is this a taxonomy?
• Inventories, catalogs,
classifications, categorization
schemas, thesauri, controlled
vocabularies
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Taxonomy not enough – need other structures
• Metadata, facets
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Taxonomies have to be used to be useful
 How to fail:
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Taxonomy as a project
Taxonomy as a search engine project afterthought
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Two Types of Taxonomies: Browse and Formal
Browse Taxonomy – Yahoo
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Browse Taxonomies: Strengths and Weaknesses
 Strengths: Browse is better than search
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Context and discovery
Browse by task, type, etc.
 Weaknesses:
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Mix of organization
• Catalogs, alphabetical listings, inventories
• Subject matter, functional, publisher,
document type
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Vocabulary and nomenclature Issues
Problems with maintenance, new material
Poor granularity and little relationship
between parts.
• Web site unit of organization
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No foundation for standards
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Formal Taxonomies: Strengths and Weaknesses
 Strengths:
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Fixed Resource – little or no maintenance
Communication Platform – share ideas, standards
Infrastructure Resource
• Controlled vocabulary and keywords
• More depth, finer granularity
 Weaknesses:
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Difficult to develop and customize
Don’t reflect users’ perspectives
• Users have to adapt to language
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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
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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
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Actors, events, functions, geography
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Taxonomy in Context: Intellectual Infrastructure
 3 infrastructures: technology, organizational, intellectual
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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
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Taxonomy in the Organization:
Project Approach or Infrastructure Approach
 Situation: Problem with access to information
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Project Approach
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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)
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Taxonomy in the Organization:
Why an Infrastructure Approach?
 Immanuel Kant
“Concepts without percepts are empty.”
– “Percepts without concepts are blind.”
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 Knowledge Management (KM) / Information
Projects
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KM without applications is empty
• Strategy only, management fad
• Elegant taxonomies – unused
 Applications without knowledge architecture (KA)
are blind
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IT based KM
– Fragmented applications
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Taxonomy in the Organization:
Structuring Content
 All kinds of content
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Structured and unstructured, Internet and desktop
 Metadata standards – Dublin core+
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Keywords - poor performance
– Need controlled vocabulary, taxonomies, semantic network
 Document Type
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Form, policy, how-to, etc.
Dynamic classification with subject matter taxonomies
 Audience
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Role, function, expertise, information behaviors
Consistent across subject matter and people
 Best bets metadata
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Taxonomy in the Organization:
Structuring People
 Individual People
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Tacit knowledge, information behaviors
Advanced personalization – category priority
• Sales – forms ---- New Account Form
• Accountant ---- New Accounts ---- Forms
 Communities
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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)
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Taxonomy in the Organization:
Structuring Processes and Technology
 Technology: infrastructure and applications
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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)
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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
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Portals, collaboration, text mining, business intelligence, CRM
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Taxonomy in the Organization:
The Integrating Infrastructure
 Starting point: knowledge architecture audit, K-Map
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Social network analysis, information behaviors
 People – knowledge architecture team
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Infrastructure activities – taxonomies, analytics, best bets
Facilitation – knowledge transfer, partner with SMEs
 “Taxonomies” of content, people, and activities
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Dynamic Dimension – complexity not chaos
Analytics based on concepts, information behaviors
 Taxonomy is the answer
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In an Infrastructure Context
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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
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Variety of taxonomies – important to know the differences, when to
use what.
 Step Two: Get a good taxonomist! (or learn)
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Library Science+ Cognitive Science + Cognitive Anthropology
 Step Three: Software Shopping
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Automatic Software – Fun Diversion for a rainy day
• Uneven hierarchy, strange node names, weird clusters
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Taxonomy Management, Entity Extraction, Visualization
 Step Four: Get a good taxonomy!
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Glossary, Index, Pull from multiple sources
– Get a good document collection
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Taxonomy Development: Tips and Techniques
Stage Two: Development and/or Customization
 Combination of top down and bottom up (and Essences)
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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
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Work toward the prototype and out and up and down
Repeat until dizzy or done
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Taxonomy Development: Tips and Techniques
Stage Three: Evaluate and Refine
 Formal Evaluation
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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
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Avoid binary levels, duplication of contrasts
Primary and secondary education, public and private
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Taxonomy Development: Tips and Techniques
Stage Three: Evaluate and Refine
 Practical Evaluation
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Test in real life application
Select representative users and documents
Test node labels with Subject Matter Experts
• Balance of making sense and jargon
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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
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Taxonomy Development: Tips and Techniques
Issues and Ideas
 Complex Topics – intersection of subject domains and
facets
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What documents are often about is the intersection
Example – China and Biotech
 Standards and Customization
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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
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Taxonomy Development: Tips and Techniques
Issues and Ideas
 Enterprise Taxonomy
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No single subject matter taxonomy
Need an ontology of facets or domains
 Enterprise Facet Model:
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Actors, Events, Functions, Locations, Objects, Information
Resources
Combine and map to subject domains
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Future Directions: Knowledge Organization
 New analytic methods
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Cognitive anthropology, history of ideas, ESNA
 New metadata schemas
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SCORM, RDF and semantic Web
Learning and knowledge objects
 New people models
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Bloom’s Taxonomy, Gardner’s 7 Intelligences
 Advanced personalization
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Community-based, cognitive-based
Adaptive, dynamic presentation variations
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Future Directions: Technology
 Taxonomies within applications
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Richer world knowledge and better learning
 Entity extraction and fact extraction
 Natural language processing (NLP) search – answers, not
document lists
 Integrated KM platform
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Creation, structure, retrieval, application, measurement
Integrated KM/KA team
Contextualizing content: related content, best bets, expertise,
communities
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Future Directions: Well-Articulated Organization
 Learning takes place throughout the system
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Smart applications – adapts to users’ and community’s
activities
Just-in-time training and performance support
 Combination of analytics and knowledge organization
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Concept-level, not document-level
Taxonomy is the brain, analytics are the eyes
 Self-knowledge – highest form of knowledge
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“Unexamined life is not worth living.” (Plato)
Unexamined, inarticulate enterprise is not worth having
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The Contextual Desktop: Document, List of
Documents, Applications Screen
 Before you view:
 When you look for information
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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
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 When you add/change content
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Suggests categorization value,
metadata values
– Routes to appropriate content and
communities
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– Prompt on unusual connections
• Pre-existing content
• Related content
• Regulatory issues
• Ask the question – route to experts?
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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
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Communities
• Search, chat, email
– Performance aids, classes
– Stories
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Sources
 Books
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Women, Fire, and Dangerous Things
• What Categories Reveal about the Mind
• Geroge Lakoff
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The Geography of Thought
• Richard E. Nisbett
 Software
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Convera Retrievalware
Inxight Smart Discovery – entity and fact extraction
 Courses
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Convera Taxonomy Certification
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Questions?
Tom Reamy
tomr@kapsgroup.com
KAPS Group
Knowledge Architecture Professional Services
http://www.kapsgroup.com