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

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Taxonomy Development An Infrastructure Model
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Presentation transcript:

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

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 – – 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.”

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 Business Case for Taxonomies: The “C” Level Problem  Pointy Head Boss – CTO, CFO, CEO – Doesn’t understand – wrong language – Taxonomy is extra – harder work will overcome – Not business critical – Not tangible – accounting bias – Does not believe the numbers – Believes he/she can do it  Need stories and figures that will connect  Need to understand their world – every case is different  Need to educate them – Taxonomy is tough and needed

8 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

9 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

10 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)

11 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

12 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

13 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.

14 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

15 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

16 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.

17 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

18 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

19 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

20 Semantics and Search: An Integrated Approach: Elements  Multiple Knowledge Structures – Facet – orthogonal dimension of metadata – Taxonomy - Subject matter / aboutness – Ontology – Relationships / Facts – Subject – Verb - Object  Software - Text analytics, auto-categorization, entity extraction  People – tagging, evaluating tags, fine tune rules and taxonomy  People – Users, social tagging, suggestions

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26 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

27 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!

Questions? Tom Reamy KAPS Group Knowledge Architecture Professional Services