1. Integrating an Enterprise Taxonomy with Local Variations Tom Reamy Chief Knowledge Architect KAPS Group http://www.kapsgroup.com Taxonomy Boot Camp

2. 2 Agenda  Introduction –  Information Environment  Research Approach  Integrated Solution – governance, technology – text analytics  Conclusions

3. 3 KAPS Group: General  Knowledge Architecture Professional Services – Network of Consultants  Partners – SAS, SAP, IBM, FAST, Smart Logic, Concept Searching – Attensity, Clarabridge, Lexalytics,  Strategy – IM & KM - Text Analytics, Social Media, Integration  Services: – Taxonomy/Text Analytics development, consulting, customization – Text Analytics Fast Start – Audit, Evaluation, Pilot – Social Media: Text based applications – design & development  Clients: – Genentech, Novartis, Northwestern Mutual Life, Financial Times, Hyatt, Home Depot, Harvard Business Library, British Parliament, Battelle, Amdocs, FDA, GAO, etc.  Applied Theory – Faceted taxonomies, complexity theory, natural categories, emotion taxonomies Presentations, Articles, White Papers – http://www.kapsgroup.comhttp://www.kapsgroup.com

4. Information Environment  Multi-National Financial Institution-10,000+  Diversity - multiple languages, cultures, information needs and behaviors, organizational cultures  Initial Application – knowledge management networks – Network definition – somewhat by subject area, but also political  Multiple applications – search, browse, web sites – Expertise location, Accounting-resource, analysis  Multiple audiences – internal and external, expert and non- expert (everyone a non-expert in something) 4

5. Approach  First step – research into variations – Use cases, levels of granularity – Common terms with different meanings  Interviews with multiple groups, roles, levels – Contextual interviews, information interviews – Taxonomy interviews – suggested terms and relationships  Analysis – taxonomies, search logs suggest facets, HR expertise descriptions, local web sites, keywords, clustering, new terms  Group sessions – representatives of multiple constituencies – talking out the differences 5

6. Approach: Use Cases to Address  Multiple Searches: Simple to complex queries 1. China 2. World Development Report 3. Monetary Policy Georgia 4. Health financing system in Colombia 5. Absolute income theory of consumption 6. Identify projects, funds allocated/spent, find lessons learned and experts 7. Experienced highway engineer to prepare Terms of Reference for a Detailed Feasibility report for a new road alignment with tunnels (68 km) in mountainous terrain in accordance with prevailing EU standards 6

7. 7 Current Environment Overview  Current form of Topics: Long and flat – 2 levels – Difficult to build on, desire for more specificity for experts and content, usability issues, no place for new topics  Multiple taxonomies – topics, organizational, Web site browse, industry codes – Partial overlaps, conflicting – Political – Social Development & Gender  Variations – official term, relationships of terms – New terms mostly at lower levels and stable structure  Cross-cutting topics – Finance of Education, Poverty

8. 8 Elements of the Solution  Taxonomy is only one part of the solution – Faceted metadata and text analytics – Enterprise taxonomy – death of?  Analysis of taxonomy – suitable for categorization & views – Structure – not too flat, not too large – Orthogonal categories – easier to tag and easier to map variations  Idea of Views – browse by local variations – map to official topics – Supported by software – Pool Party – Role-based views, Activity-based views  Solution: integration of multiple components – two critical

9. 9 Text Analytics – power and flexibility  Critical – Text Analytics tool – Same taxonomy term but different criteria, rules – Documents tagged for different uses, audiences  Education – for specialists – Deep complex rules, very fine granularity, specialists jargon- acronyms  Education – for generalists – High level rules, general terms, simple  Education within Social Development – Generalist rules plus social development terms – birth weight

10. 10 Proposed Model for a Taxonomy Eco-System 2. Other facets to describe Networks and other objects: 1. Industry 2. Programs 3. Methods 4. Business activity 5. Organization 6. Skills / Expertise 7. Other ? 3. Leveraging existing Metadata:  Document type  Project  Product +  Geography + 4. Combined with data:  Expert Profiles-Projects, etc.  Authored documents, etc.  Data Modules of all kinds 1. Subject / Topic: Revised Topic Taxonomy – integrated

11. 11 Governance Critical Elements  Strategic Level – Council(s) – Set overall content policy and strategies including explicit criteria for taxonomy terms and changes to terms – Set organizational structure  Management / Operational Level – Changes in taxonomy, user feedback, applications  Communication – implementation, value-ROI of taxonomy, promote awareness  Technology – Taxonomy Management, Text Analytics, Applications – coordination IMT & taxonomy team  Research – new applications of taxonomy & text analytics

12. 12 Critical Success Factors: Governance  Governance Policy & Process & Enforcement – Incorporate enforcement into publishing process / Hybrid Auto-cat  Taxonomy management is part of overall information management with additional taxonomy roles/functions  Best Practice: combination of central and distributed teams  Taxonomy specific: Taxonomy Manager – Central & Networks – Revise tax structure, rules for changes, manage implementation – Enforcement – combination of central & Networks  Feedback – metrics – identify need for new terms, remove old terms – Combination of user feedback in application & periodic analysis

13. Conclusion  Taxonomies are an enterprise resource  Danger of monolithic over-riding local variations – Less useful and/or ignored  Danger of chaos of multiple variations losing ability to coordinate and communicate  Solution: Research into users, use cases, semantic resources  Integrated solution – importance of distributed governance  Integrated solution – text analytics to reflect local variations and provide a means to integrate into unified solution  Facets, text analytics and browse views solve 75%, rest is manageable  No one was entirely happy – must be doing something right 13

14. Questions? Tom Reamy tomr@kapsgroup.com KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com www.TextAnalyticsWorld.comwww.TextAnalyticsWorld.com March 17-19, San Francisco