Expanding Enterprise Roles for Librarians

1. Expanding Enterprise Rolesfor Librarians Tom ReamyChief Knowledge Architect KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com

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

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. 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. Knowledge ArchitectureBasic 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. Knowledge Architecture: ServicesCentral 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. 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. 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. Librarians Essential to ProjectLessons 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. Lessons for LibrariansFocus 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. Lessons for LibrariansFocus 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. 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. 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 Reamytomr@kapsgroup.com KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com