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Taxonomy Development An Infrastructure Model

Taxonomy Development An Infrastructure Model. Tom Reamy Chief Knowledge Architect KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com. Agenda. Introduction The Enterprise Context Making the Business Case Infrastructure Model of Taxonomy Development

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Taxonomy Development An Infrastructure Model

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  1. Taxonomy DevelopmentAn Infrastructure Model Tom ReamyChief Knowledge Architect KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com

  2. Agenda • Introduction • The Enterprise Context • Making the Business Case • Infrastructure Model of Taxonomy Development • Taxonomy in 4 Contexts • Content, People, Processes, Technology • Infrastructure Solutions – the Elements • Conclusion

  3. 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

  4. Business Case for Taxonomies:IDC White Paper • Information Tasks • Email – 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. 30-40% of a knowledge worker’s time is spent managing documents.”

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

  6. 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?

  7. Infrastructure Model of Taxonomy DevelopmentTaxonomy 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

  8. Taxonomy in ContextStructuring 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

  9. 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)

  10. 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

  11. 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

  12. 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.

  13. Infrastructure Solutions: The start and foundationKnowledge 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

  14. Infrastructure Solutions: ResourcesPeople 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

  15. 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.

  16. Infrastructure Solutions: ResourcesPeople 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

  17. Infrastructure Solutions: ResourcesPeople 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

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

  19. 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

  20. 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!

  21. Questions? Tom Reamytomr@kapsgroup.com KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com

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