1. Unstructured Content Management Taxonomic Publishing Models Tom Reamy Chief Knowledge Architect KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com tomr@kapsgroup.com

2. 2 Agenda  KAPS Group and Knowledge Architecture  Current State of Content Management  Taxonomies and Content Management – What, Why, and How  Taxonomic Content Management  Infrastructure Content Management – Technology, Teams, Taxonomies – Beyond Taxonomies Knowledge Objects, Semantic Web, Personas, etc.

3. 3 KAPS Group  KAPS Background – Knowledge Architecture Consultants – Intellectual Infrastructure: Content, Tools, People E-Learning and Information Architecture Knowledge Architecture Audit Social Network Analysis and Business Process – Professional Services partner to Search, Content Management & Categorization Companies

4. 4 Current State of Content Management  Forrester Research: – Current content management systems are “immature”. – High Cost, Proprietary technology – Poor implementation, Difficult to maintain & customize  CM is good at: – Software, system integration – Version control, work flow – Decoupling content and presentation  Part of a Broader problem – Delphi Survey 68% finding information is difficult 50% spend more than 2 hours a day looking

5. 5 Current State of Content Management  Content Management – Strong on management, weak on content – Content is a black box – simply moved around  What is missing is the meaning dimension – In-depth and articulated understanding of content  Perceived Solution – Delphi Survey – Taxonomy – 90% plan on taxonomy strategy in 24 months – 76% taxonomy is important  Taxonomy: necessary but not sufficient

6. 6 Content Management and Taxonomy: What?  Formal Taxonomies – Linnaeus – Taxonomy of life – Only relationship is “Is Kind Of”  Browse Taxonomies (Informal) – Yahoo – Hierarchical – Variety of relationships  Classifications and Categorization  Metaphorical Taxonomies – Thesaurus, catalog, index, site map

7. 7 Content Management and Taxonomy: What?  What makes a good taxonomy? – Formal: Quality Metrics Corpus, Coverage, Nomenclature, terminology, dependency Mixed classes, verbal forms, bad speciation, etc. Bell Curve, balance of depth and width – Informal: An understandable organization of content that enables people to find information and which supports knowledge discovery. Creates a context within which facts are related Find, Identify, Describe information, relations, context

8. 8 Content Management and Taxonomy: What?  Taxonomy as part of knowledge organization  Metadata: Dublin Core+ – CM functions: Language, Identifier, Rights – Combination functions: Publisher, Author – Subject matter functions: keywords, descriptions Minimum need controlled vocabularies  Contextual – DocumentObjectType, AudienceType  Facets and entities – People, Companies, Compounds, Geography – Multiple views into content – Dynamic Mapping of facets

9. 9 Content Management and Taxonomy: Why?  Search Stinks – Integrated Browse and Search works better than search Ecommerce – 56% of all searches fail = lost income Intranet = lost time, lost business, lost ideas Taxonomic CM - Rich semantic web of concepts, not a unstructured collection of documents  Cost of poor Search and Content Management If its not organized,you can’t find it. If you can’t find it, you can’t use it. If you can’t find it, you waste a lot of time. If you can’t find it, you could lose an account. If you can’t find it, you could look stupid. If you can’t find it, it doesn’t exist.

10. 10 Content Management and Taxonomy: Why?  In 2 years, categorization will replace search  Categorization will be a component/foundation for: – Search, content management, portals, CRM, collaboration, etc.  Beyond browse – Agent profiles – just in time news – Intelligent agents – semantic web – Contextualized search results – Personalization within communities

11. 11 Content Management and Taxonomy: How?  Old Answer: Manual hire a bunch of librarians and IA’s Costly, difficult to maintain Use SME’s Costly, difficult to maintain, bad track record  New Answer: Integrate Manual and new software Integrate Content Management and Taxonomy Integrate central team and local authors

12. 12 Content Management and Taxonomy: How?  New Technologies – Unstructured Data Management – Taxonomy Management – Smart Categorization, summarization – Entity Extraction and metadata generation – Visualization of taxonomic relationships – Linguistic analysis, not just bag of words

13. 13 Machine-Categorization: Methods  Semi-Automatic: Rules, If-Then Maximum precision & flexibility  Catalog by Example: Bayesian, SVM, Neural Training Sets (5-500) Speed, Learning  Statistical Clustering – Set of Documents & Taxonomy Level  Semantic Analysis & World Knowledge

14. Machine Categorization: The Human Element  Automatic Categorization is Not  Humans are better, but not as consistent – Bring outside contexts to the document Purpose, similar documents, common sense – Understandable mistakes  Computers are faster and cheaper  Categorization is part of knowledge organization – Meta data, communities, taxonomies, etc.  The Best Answer is Hybrid or Cyborg Categorization

15. 15 Taxonomic Content Management: Standard View Send email request to CT to review Site Owner Pulls Files from Staging Server Makes Edits and Changes Send files to staging server Central Team Test Files (QA) Move Files to Pre- Prod Move to Production

16. 16 Taxonomic Content Management: Taxonomic View Send email request to CT to review Authors Pulls Files from Staging Server Makes Edits and Changes Send files to staging server Central Team Test Files (QA) Categorization MetaData Move Files to Pre- Prod Move to Production Categorization MetaData Taxonomies: Content, Communities, Tasks

17. 17 Taxonomic Content Management: Work Flow with Meaning  Preliminary Foundation Work – Design the ontology – Develop taxonomies – Design metadata standards – Collaborative development of controlled vocabularies  Authors, SME’s – check document in: – Have a summary either written by human or software – List of metadata suggestions, entities – people, places, etc. – Provisional categorization – Decision: publish or submit for review, central team or community of experts. – Request for additional keywords or categorization issues

18. 18 Taxonomic Content Management: Work Flow with Meaning  Central Team – Review documents – easier, faster – Use summaries, metadata, entities to provide context – Review infrastructure requests – new keywords, categories  Integrated Work Flow – Strengths of local and central – Variety of roles, flexible (few dedicated roles needed). – Collaborative categorization and keywords by SME, software, and central team SME’s can function as central team

19. 19 Taxonomic Content Management: Work Flow with Meaning  Publish by Category, not web site – Web site is a terrible unit of organization of content – 10 to 10,000 documents – Who published is only one dimension  Flexible & Intelligent Publishing – Collaboration supported across organization – Dynamically generate views, facets, web sites – Supports intelligent personalization Requires metadata to go beyond idiosyncratic views of content – Prompt on unusual connections Pre-existing, categories Regulatory or legal issue

20. 20 Taxonomic Content Management: Work Flow with Meaning  Content Reorganization – Category + Publisher = related document sets – Rich web of related content Content + background contexts Legal/Policy contexts Technical contexts Customer / Task contexts – Support browse by topic, type, task, entity, facets

21. 21 Taxonomic Content Management: Work Flow with Meaning  Design even more important – Taxonomic effort – Balance of pre-defined and dynamic – Broader context of content, communities, processes  CM companies are developing or buying taxonomic capabilities – Metadata, categorization, summarization, etc.  CM as a platform technology – Article – EContent October – KM and E-Learning – CM, LCMS, LMS, KM platform  CM: Beyond Categorization – Collaboration: E-Room, Intraspect – Search and Portals: Epicentric  CM as part of Intellectual Infrastructure

22. 22 Infrastructure Content Management Technology, Teams, Taxonomies  Technology – CM -- Least important – unless you get it wrong – Taxonomic Software Support articulation of intellectual infrastructure Integrated with CM – supports maintenance – KM Platform – CM in Context Search, Portals, Collaboration Supports application of the intellectual infrastructure

23. 23 Infrastructure Content Management Technology, Teams, Taxonomies  Teams – Where?  Best: Central, Dedicated Department – Cross Organizational, Multidisciplinary  Part Time, Distributed SME’s, Business owners – Practical, real world input  Partners: IT, HR, Corporate Communication, Library, Training  Worst: IT Project Manger, Intranet programming team

24. 24 Infrastructure Content Management Technology, Teams, Taxonomies  Teams – Who?  Knowledge Architect and Learning Object Designers  Knowledge Engineers and curriculum developers  Knowledge Facilitators and Trainers  IT, Web developers, application programmers  Librarians and information architects  Business analysts and project managers  Corporate Communication writers and editors

25. 25 Infrastructure Content Management Technology, Teams, Taxonomies  Teams – What?  Infrastructure Activities – Integrate taxonomy across the company Content, communities, activities – Grow and Develop taxonomies Taxonomy metrics require skill to fix problems – Design content repositories, update and adapt categorization – Package knowledge into K objects, combine with stories, learning histories – Metrics and Measurement – analyze and enhance – Knowledge Architecture Audit – Cognitive Difference – Geography of Thought Panda, monkey, banana

26. 26 Infrastructure Content Management Technology, Teams, Taxonomies  Taxonomies and Beyond:  Intellectual infrastructure – Context for CM  Taxonomy of Communities – Map of formal and informal communities – Social Network Analysis, Personas – Community specific vocabularies – Integrate with knowledge objects, metadata  Expertise Location, mentoring, story telling  Communities of Practice  Training – Embedded Learning - Just-In-Time, Performance Support

27. 27 Infrastructure Content Management Technology, Teams, Taxonomies  Taxonomies and Beyond:  Document not the best unit of organization in all situations  Learning/Knowledge Objects – Chunks of content and XML metadata – Reusable, flexible, answer machines – Important of context – rules for relating objects  Advanced MetaData – SCORM+ Semantic Density, typical learning time – RDF and Semantic Web subClassOf, seeAlso, isRelatedTo

28. 28 ICM and Applications: Contextualizing Content  Knowledge Creating – Innovation, E-learning, LMS – Collaboration Distributed Categorization, Community Vocabularies  Knowledge Sharing / Transmission – Collaboration, Retrieval – content and experts  Knowledge Using – Smart Applications, Portals – CRM, Data warehouse, text mining, business intelligence

29. 29 ICM and Applications: Contextualizing Content  Knowledge = information + contexts  Contexts are what gives depth and meaning to information – Let me tell you a story  Contextualizing Content – Related topics, contexts, content types – Rules for relating, integrating contexts

30. 30 Knowledge Retrieval: Contexts  Search for product name – List of documents that are explicitly about the product – Category Views Features of the product Product comparisons Legal or policy documents – Background Resources List of Experts, communities Glossaries, internal libraries

31. 31 Knowledge Retrieval: Contexts  Search for product name – Search and Browse options – Text or visual options – Offers a variety of contexts: Related content, best bests (community based and input form central team) – Learns from my behavior and community behavior – Usage Analytics – based on meaning, not counting clicks

32. 32 Knowledge Retrieval: Contexts  Search for product name – Filters Admin in retail tech support Belong to a discussion group Last time I looked up product information, I looked at certain documents and types I don’t want legal information emphasized and I’m not an expert on this product

33. 33 Summary  Successful Content Management requires a taxonomic dimension  CM companies have recognized this and added features  Next Step: Content management as infrastructure platform  Need: well articulated intellectual infrastructure  3 important terms: Contexts, Taxonomies, Intellectual Infrastructure  Your choice – go back to file management or forward to infrastructure content management

34. Questions? Tom Reamy tomr@kapsgroup.com KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com