Presentation on theme: "Taxonomy Development in an Enterprise Context Tom Reamy Chief Knowledge Architect KAPS Group Knowledge Architecture Professional Services"— Presentation transcript:
Taxonomy Development in an Enterprise Context Tom Reamy Chief Knowledge Architect KAPS Group Knowledge Architecture Professional Services
2 Agenda Introduction The Enterprise Context – Making the Business Case – Beyond Search and Taxonomy Projects 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, 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 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
5 Business Case for Taxonomies: The Right Context Taxonomies are an Infrastructure Resource Right context – business case and development – Not as a stand alone project Economist June 9, 2005: – Overdue and over budget, over and over again. – Companies are increasingly keen on projects. – Why? When so many of them fail. Failure to integrate all relevant contexts Under-developed understanding of contexts Closure is an illusion.
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 Right Context – Resources Integrated Enterprise requires both an infrastructure team and distributed expertise. – Software and SMEs 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 Advanced Cognitive Differences – Panda, monkey, banana Infrastructure as Operating System – Word vs. Word Perfect – Instead of sharing clipboard, share information and knowledge.
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 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
14 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
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: 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
17 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
18 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
19 Infrastructure Solutions: Taxonomy Development Initial Development / 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 Map the taxonomy to communities and activities – Category differences – Vocabulary differences
20 Infrastructure Solutions: Taxonomy Development 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 Practical Evaluation – Test in real life application – Test node labels with Subject Matter Experts, representative users and documents – 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 Infrastructure Solutions: Taxonomy Development Issues and Ideas 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
22 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
23 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