1. Knowledge Architecture Process & Case Studies Tom Reamy Chief Knowledge Architect KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com

2. 2 Agenda  Introduction  KA and Library Science – Taxonomy Development – Expertise Location, Collaboration  Tale of Two Taxonomies – Best of Times and Worst of Times  Conclusion

3. 3 Taxonomy Development Process  Foundation – Strategic & Business Context – Info problems, political environment – support, special interests  Knowledge Architecture Audit – Knowledge Map  Taxonomy Strategy/Model – forms, technology, people – Existing taxonomic resources, software  Draft Taxonomy – Information Interviews, focus groups, card sorts – Content Analysis, top down & bottom up – Refine, feedback, pilot app  Taxonomy Plans – Governance, Maintenance, Applications

4. 4 Knowledge Architecture Audit: Knowledge Map Project Foundation Contextual Interviews Information Interviews App/Content Catalog User SurveyStrategy Document Meetings, work groups Overview High Level: Process Community Info behaviors of Business processes Technology and content All 4 dimensions Meetings, work groups General Outline Broad Context Deep Details Complete Picture New Foundation

5. 5 Taxonomy Development Process: Progressive Refinement Taxonomy Model Information Interviews Content Analysis RefineMap Community Governance Plan Buy/Find work groups Overview Info behaviors, Card Sorts Bottom Up Prototypes Interviews Evaluate Refine Interviews Develop, Refine General Outline Preliminary Taxonomy Taxonomy 1.0 Taxonomy 1.0-1.9 Tax 2.0Taxonomy

6. 6 Taxonomy Development: 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

7. 7 Taxonomy Development: Process  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

8. 8 Taxonomy Development Evaluate and Refine  Formal Evaluation – Quality of corpus – size, homogeneity, representative – Breadth of coverage – main ideas, outlier ideas – Structure – balance of depth and width – Evaluate speciation steps – understandable and systematic Person – Unwelcome person – Unpleasant person - Selfish person  Facetize a formal taxonomy – Look for duplications Example - Methods – chemistry, physics, social studies

9. 9 Taxonomy Development: 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

10. 10 Enterprise Environment – Case Studies  A Tale of Two Taxonomies – It was the best of times, it was the worst of times  Basic Approach – Initial meetings – project planning – High level K map – content, people, technology – Contextual and Information Interviews – Content Analysis – Draft Taxonomy – validation interviews, refine – Integration and Governance Plans

11. 11 Enterprise Environment – Case One – Taxonomy, 7 facets  Taxonomy of Subjects / Disciplines: – Science > Marine Science > Marine microbiology > Marine toxins  Facets: – Organization > Division > Group – Clients > Federal > EPA – Instruments > Environmental Testing > Ocean Analysis > Vehicle – Facilities > Division > Location > Building X – Methods > Social > Population Study – Materials > Compounds > Chemicals – Content Type – Knowledge Asset > Proposals

12. 12 Enterprise Environment – Case One – Taxonomy, 7 facets  Project Owner – KM department – included RM, business process  Involvement of library - critical  Realistic budget, flexible project plan  Successful interviews – build on context – Overall information strategy – where taxonomy fits  Good Draft taxonomy and extended refinement – Software, process, team – train library staff – Good selection and number of facets  Final plans and hand off to client

13. 13 Enterprise Environment – Case Two – Taxonomy, 4 facets  Taxonomy of Subjects / Disciplines: – Geology > Petrology  Facets: – Organization > Division > Group – Process > Drill a Well > File Test Plan – Assets > Platforms > Platform A – Content Type > Communication > Presentations  Issues – Not enough facets – Wrong set of facets – business not information – Ill-defined facets – too complex internal structure

14. 14 Enterprise Environment – Case Two – Taxonomy, 4 facets  Environment Issues – Value of taxonomy understood, but not the complexity and scope – Under budget, under staffed – Location – not KM – tied to RM and software Solution looking for the right problem – Importance of an internal library staff – Difficulty of merging internal expertise and taxonomy

15. 15 Enterprise Environment – Case Two – Taxonomy, 4 facets  Project Issues – Project mind set – not infrastructure – Wrong kind of project management Special needs of a taxonomy project  Research Issues – Not enough research – and wrong people – Misunderstanding of research – wanted tinker toy connections Interview 1 implies conclusion A

16. 16 Taxonomy Development Conclusion: Risk Factors  Political-Cultural-Semantic Environment – Not simple resistance - more subtle – re-interpretation of specific conclusions and sequence of conclusions / Relative importance of specific recommendations  Understanding project scope  Access to content and people – Enthusiastic access  Importance of a unified project team – Working communication as well as weekly meetings

17. 17 Conclusion: Lessons for Librarians  Size Matters – but bigger is not better  No single enterprise taxonomy  Faceted taxonomies – expose different parts to different groups  Corporate taxonomies are not like Dewey decimal system – Taxonomy not a classification – Smaller – easier to use – Get breadth of coverage with facets not single subject taxonomy

18. 18 Conclusion: Lessons for Librarians Information Architecture Lessons  Focus on user – Developing classification for novice and infrequent user – Usability – develop understanding and different relationships – continuous monitoring and refining  No right way to categorize – understand variations  There is no shelf – equal numbers of categories not books in each category  Focus on applications and usability

19. 19 Conclusion: Lessons for Librarians Expand You World  Cognitive Science – Modeling how people think, categorize  Business Activities – Information behaviors within context of business acitvities  Technology – CM – metadata – standards and implementation – Search – facets + taxonomy + best bets + – Text Analytics – learn to develop categorization rules – Taxonomy Management Software - necessary

20. 20 General Conclusion: Taxonomy Development  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

21. 21 General Conclusions – KA and Library  Knowledge Architecture – new foundation for KM – Key is models of knowledge  Knowledge Architecture – new direction for librarians – A Key is expanding into the organization – business value – A Key is focus on users – IA + cognitive science  Big Issues: – External and Internal resources – balance of partnering and extending each group  Knowledge Architecture is a bridge between KM and Library Science

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