1. Expanding Enterprise Roles for Librarians Tom Reamy Chief Knowledge Architect KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com

2. 2 Agenda  Introduction  Knowledge Architecture – the Foundation – Knowledge Architecture Projects & Services  Case Study – Expertise location and Taxonomy  From Librarian to Knowledge Architect  Conclusions

3. 3 KAPS Group: General  Knowledge Architecture Professional Services  Virtual Company: Network of consultants – 12-15  Partners – Inxight, Teragram, Smart logic, Lexalytics, Access Innovation, Endeca, FAST, Interwoven, etc.  Consulting, Strategy, Knowledge architecture audit  Services: – Taxonomy development, consulting, customization – Technology Consulting – Search, Text Analytics, CMS, Portals, etc. – Metadata standards and implementation – Knowledge Management: Collaboration, Expertise, e-learning – Applied Theory – Faceted taxonomies, complexity theory, natural categories

4. 4 What is Knowledge Architecture?  Knowledge Architecture is an interdisciplinary field that is concerned with designing, creating, applying, and refining an infrastructure for the flow of knowledge throughout an organization.  Knowledge Architecture is library science + information architecture + cognitive science + history of ideas + ?  Essential Partner – Education (Knowledge transfer)  Knowledge Architecture is a bridge between KM and Library Science

5. 5 Knowledge Architecture Basic 4 Contexts of Structure  Ideas – Content Structure – Taxonomies, metadata, facets, ontologies, etc. – Applications - exchange meaning, not data  People – Company Structure – Communities, Users, Central Team  Organizational activities, business processes, events, etc. – Central team - establish standards, facilitate  Technology Layer – Text Analytics / taxonomy tools, CMS, Search, portals – Applications – BI, CI, Text Mining

6. 6 Knowledge Architecture: Services Central Team + Software: Services  Foundation services: Knowledge architecture audit – Enterprise wide and/or project scale  Integrate taxonomy across the company – Input into technology decisions – semantics  Traditional Taxonomy Services – Creating, acquiring, refining taxonomies – Facilitating metadata creation – human and software  Create a framework for 2.0 – Meld folksonomies and taxonomies – Expertise, Community taxonomies, search still needed

7. 7 Case Study: Expertise Location / Taxonomy  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

8. 8 Case Study: Expertise Location  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

9. 9 Librarians Essential to Project Lessons for Librarians: Content Structures  No single enterprise taxonomy – Small Formal Taxonomies  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 – Faceted taxonomies – expose different parts to different groups

10. 10 Lessons for Librarians Focus on Users / Cognitive Science  Focus on user / usability – Developing classification for novice and infrequent user – Usability – continuous monitoring and refining  No right way to categorize – understand variations  Monkey, Banana, Panda  Typicality / Prototype– Robin vs. Ostrich  Basic Level Categories: Mammal – Dog – Golden Retriever – Balance of Distinctiveness and # of Properties (informativeness) – Level of Expertise = One higher or lower

11. 11 Lessons for Librarians Focus on Business and Technology  Business Activities – Information behaviors within context of business activities  Technology – CM – metadata – standards and implementation – Search – facets + taxonomy + best bets + clustering – Text Analytics – learn to develop categorization rules – Taxonomy Management Software - necessary

12. 12 Conclusion  Knowledge Architecture is a new foundation for KM – KA brings knowledge and knowledge structures back to KM – And is a great avenue for librarians to expand roles  KA is an infrastructure solution, not a project  Build on core knowledge organization – Add user focus, cognitive science, business activity and technology  A strong theoretical foundation is important and practical  Web 2.0/Folksonomies are not the answer

13. 13 Resources  Books – Women, Fire, and Dangerous Things – George Lakoff – Knowledge, Concepts, and Categories Koen Lamberts and David Shanks – The Stuff of Thought – Steven Pinker – The Mind and Its Stories – Patrick Colm Hogan  Articles – The Power of Stories – Scientific American Mind – August/September 2008 – Folksonomy Folktales – KMWorld October 2009

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