Expanding Enterprise Rolesfor Librarians

Tom ReamyChief Knowledge Architect

KAPS GroupKnowledge Architecture Professional Services

http://www.kapsgroup.com

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Agenda Introduction

Knowledge Architecture – the Foundation– Knowledge Architecture Projects & Services

Case Study – Expertise location and Taxonomy

From Librarian to Knowledge Architect

Conclusions

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

Questions? Tom Reamy

tomr@kapsgroup.comKAPS Group

Knowledge Architecture Professional Serviceshttp://www.kapsgroup.com