1. Integrating an Enterprise Taxonomy with Local Variations Tom Reamy Chief Knowledge Architect KAPS Group Program Chair – Text Analytics World Knowledge Architecture Professional Services http://www.kapsgroup.com

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

3. 3 Introduction: KAPS Group  Knowledge Architecture Professional Services – Network of Consultants  Applied Theory – Faceted & emotion taxonomies, natural categories Services: – Strategy – IM & KM - Text Analytics, Social Media, Integration – Taxonomy/Text Analytics, Social Media development, consulting – Text Analytics Quick Start – Audit, Evaluation, Pilot  Partners – Smart Logic, Expert Systems, SAS, SAP, IBM, FAST, Concept Searching, Attensity, Clarabridge, Lexalytics  Clients: Genentech, Novartis, Northwestern Mutual Life, Financial Times, Hyatt, Home Depot, Harvard Business Library, British Parliament, Battelle, Amdocs, FDA, GAO, World Bank, Dept. of Transportation, etc.  Program Chair – Text Analytics World – March 29-April 1 - SF  Presentations, Articles, White Papers – www.kapsgroup.comwww.kapsgroup.com  Current – Book – Text Analytics: How to Conquer Information Overload, Get Real Value from Social Media, and Add Smart Text to Big Data

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. 6 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

7. 7 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- Governance and Text Analytics

8. Mid-tier layer Information Services/Semantic Layer Enterprise Information Integration Analysis & Reporting Enterprise search engine Data mining, Text Analytics engine Statistical Analysis Predictive Analytics Front-end application DashboardAd-hoc queryMobile AppsPortals/webLoB Client UIMashupsEnterprise Search UI Metadata Mgt Web content EmailDocumentsBusiness data Structured Data Statistical data Structured Data Shared drives Vocabularies Taxonomies Reference Data Core Metadata Corporate data Model Reference Architecture Governance Consolidated Repositories Metadata Repository/ Registry Operational Data Store Data Warehouse Master Data Data marts Unstructured data Information Standards & Policy Multilingual Data Sources Unstructured data External External Data Data Movement ETLData ServicesESB… Data processing engine (e.g Hadoop) e-publish, Day, Drupal, blogs etc Wbdocs, Jolis SAP, PeopleSoft, Finance etc Jive Sharepoint Factiva News Research dbs DDP

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  New Topic Taxonomy – Enhanced structure and coverage – deeper framework to build on – Implemented in new software – flexible, solves old debates – Facets – remove complexity, increase coverage – 10 X 10. – Powered by auto-categorization - tagging, advanced applications – Combine with current data –HR (Expertise), other  Taxonomy is part of an integrated information management – Search, Content management, IM Policy, External Web, etc.  Facets – Subject (topic), Industry, Program, Methods, Business Activities, Organization, Skills, Document Type, Project, Product, Geography

11. Governance Structure Executive Function Sponsorship Tax Management Central Tax Management (Anchors & Regions) Users & SMEs Taxonomy Management IM focal Point, KM, web etc (Anchors & Regions, IMT) Revise/approve tax structure Rules for changes Text Analytics/Research Manage implementation Gather & make changes Content & tagging analysis Coordinate feedback Communication / Training Provide feedback Feedback loop Set overall policy and strategies Drive direct acceptance IT Systems Coordinate changes in dependent systems Working Group Prioritize changes, cross-cutting Strategic Level Integration with existing Information Management Operational Resource Decisions Organizational structure

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 29-April 1, San Francisco