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Taxonomy and Knowledge Organization Taxonomy in Context

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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 KAPS Group
Knowledge Architecture Professional Services

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