Taxonomy Development An Infrastructure Model Tom Reamy Chief Knowledge Architect KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com

Agenda Introduction Type of Taxonomies The Enterprise Context Making the Business Case 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

KAPS Group Knowledge Architecture Professional Services (KAPS) Consulting, strategy recommendations Knowledge architecture audits Partners – Convera, Inxight, FAST, 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.

Two Types of Taxonomies: Browse and Formal Browse Taxonomy – Yahoo

Two Types of Taxonomies: Formal

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

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

Facets and Dynamic Classification Facets are not categories Entities or concepts belong to a category Entities have facets Facets are metadata - properties or attributes Entities or concepts fit into one category All entities have all facets – defined by set of values Facets are orthogonal – mutually exclusive – dimensions An event is not a person is not a document is not a place. Facets – variety – of units, of structure Date or price – numerical range Location – big to small (partonomy) Winery – alphabetical Hierarchical - taxonomic

Faceted Navigation: Strengths and Weaknesses More intuitive – easy to guess what is behind each door 20 questions – we know and use Dynamic selection of categories Allow multiple perspectives Trick Users into “using” Advanced Search wine where color = red, price = x-y, etc.. Weaknesses: Difficulty of expressing complex relationships Simplicity of internal organization Loss of Browse Context Difficult to grasp scope and relationships Limited Domain Applicability – type and size Entities not concepts, documents, web sites

Dynamic Classification / Faceted navigation 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

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

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.”

Business Case for Taxonomies: IDC White Paper Time Wasted Reformat information - $5.7 million per 1,000 per year (400M) Not finding information - $5.3 million per 1,000 (370M) Recreating content - $4.5 Million per 1,000 (315M) Small Percent Gain = large savings 1% - $10 million 5% - $50 million 10% - $100 million

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?

Ideas – Content Structure 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

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

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)

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

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

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.

Knowledge Map - Understand what you have, what you are, what you want 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

Knowledge Architect and learning object designers 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

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.

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

KM/KA Dept. – Cross Organizational, Interdisciplinary 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

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

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

Infrastructure Solutions: Taxonomy Development Stage Two: Taxonomy Model 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

Combination of top down and bottom up (and Essences) Taxonomy Development: Tips and Techniques Stage Three: 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 Map the taxonomy to communities and activities Category differences Vocabulary differences

Taxonomy Development: Tips and Techniques Stage Four: 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

Taxonomy Development: Tips and Techniques Stage Four: 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

Sources Books Software Courses Women, Fire, and Dangerous Things What Categories Reveal about the Mind George Lakoff The Geography of Thought Richard E. Nisbett Software Convera Retrievalware Inxight Smart Discovery – entity and fact extraction Courses Convera Taxonomy Certification

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

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 tomr@kapsgroup.com KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com