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Enterprise Semantic Infrastructure Workshop . Tom Reamy Chief Knowledge Architect KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com. Agenda. Introduction Semantic Infrastructure Basic Concepts – Content, People, Business Processes, Technology

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Enterprise semantic infrastructure workshop

Enterprise Semantic Infrastructure Workshop

Tom ReamyChief Knowledge Architect

KAPS Group

Knowledge Architecture Professional Services

http://www.kapsgroup.com


Agenda
Agenda

  • Introduction

  • Semantic Infrastructure

    • Basic Concepts – Content, People, Business Processes, Technology

    • Developing an Articulated Strategic Vision

    • Benefits of an Infrastructure Approach

  • Development and Maintenance of a Semantic Infrastructure

    • Semantic Tools – Capabilities & Acquisition Strategy

    • Development Processes & Best Practices

  • Semantic Infrastructure Applications

    • Enterprise Search

    • Search Based Applications & Beyond

  • Discussion &Questions


Kaps group general
KAPS Group: General

  • Knowledge Architecture Professional Services

  • Virtual Company: Network of consultants – 8-10

  • Partners – SAS, Smart Logic, Microsoft, Concept Searching, etc.

  • Consulting, Strategy, Knowledge architecture audit

  • Services:

    • Taxonomy/Text Analytics development, consulting, customization

    • Technology Consulting – Search, CMS, Portals, etc.

    • Evaluation of Enterprise Search, Text Analytics

    • Metadata standards and implementation

    • Knowledge Management: Collaboration, Expertise, e-learning

  • Applied Theory – Faceted taxonomies, complexity theory, natural categories


Semantic infrastructure basic concepts benefits

Semantic InfrastructureBasic Concepts & Benefits

Tom ReamyChief Knowledge Architect

KAPS Group

Knowledge Architecture Professional Services

http://www.kapsgroup.com


Agenda1
Agenda

  • Semantic Infrastructure – Basic Concepts

    • Content & Content Structure

    • People – Resources, Producers, Consumers

    • Semantics in Business Processes

    • Technology – Information, Text Analytics, Text Mining

  • Semantic Infrastructure – Strategic Foundation

    • Knowledge Audit Plus

  • Semantic Infrastructure – Benefits of an Infrastructure Approach

    • Infrastructure vs. Projects

    • Semantics vs. Technology

  • Conclusion


Semantic infrastructure 4 dimensions
Semantic Infrastructure: 4 Dimensions

  • Ideas – Content and Content Structure

    • Map of Content – Tribal language silos

    • Structure – articulate and integrate

  • People – Producers & Consumers

    • Communities, Users, Central Team

  • Activities – Business processes and procedures

    • Semantics, information needs and behaviors

  • Technology

    • CMS, Search, portals, text analytics

    • Applications – BI, CI, Semantic Web, Text Mining


Semantic infrastructure 4 dimensions content and content structure
Semantic Infrastructure: 4 Dimensions Content and Content Structure

  • Map multiple types and sources of content

    • Structured and unstructured, internal and external

  • Beyond Metadata and Taxonomy

    • Keywords - poor performance

    • Dublin Core: hard to implement

    • Dublin Core: Too formal and not formal enough

  • Need structures that are more powerful and more flexible

    • Model of framework and smart modules

  • Framework

    • Faceted metadata

    • Simple taxonomies with intelligence – categorization & extraction

    • Ontology and Semantic Web

    • Best bets and user metadata


Knowledge structures
Knowledge Structures Structure

  • List of Keywords (Folksonomies)

  • Controlled Vocabularies, Glossaries

  • Thesaurus

  • Browse Taxonomies (Classification)

  • Formal Taxonomies

  • Faceted Classifications

  • Semantic Networks / Ontologies

  • Categorization Taxonomies

  • Topic Maps

  • Knowledge Maps


A framework of knowledge structures
A Framework of Knowledge Structures Structure

  • Level 1 – keywords, glossaries, acronym lists, search logs

    • Resources, inputs into upper levels

  • Level 2 – Thesaurus, Taxonomies

    • Semantic Resource – foundation for applications, metadata

  • Level 3 – Facets, Ontologies, semantic networks, topic maps, Categorization Taxonomies

    • Applications

  • Level 4 – Knowledge maps

    • Strategic Resource


Semantic infrastructure people
Semantic Infrastructure: People Structure

  • Communities / Tribes

    • Different languages

    • Different Cultures

    • Different models of knowledge

  • Two needs – support silos and inter-silo communication

  • Types of Communities

    • Formal and informal

    • Variety of subject matters – vaccines, research, sales

    • Variety of communication channels and information behaviors

  • Individual People – tacit knowledge / information behaviors

    • Consumers and Producers of information – In Depth

    • Map major types


Semantic infrastructure dimensions people central team
Semantic Infrastructure Dimensions StructurePeople: Central Team

  • Central Team supported by software and offering services

    • Creating, acquiring, evaluating taxonomies, metadata standards, vocabularies, categorization taxonomies

    • Input into technology decisions and design – content management, portals, search

    • Socializing the benefits of metadata, creating a content culture

    • Evaluating metadata quality, facilitating author metadata

    • Analyzing the results of using metadata, how communities are using

    • Research metadata theory, user centric metadata

    • Facilitate knowledge capture in projects, meetings


Semantic infrastructure dimensions people location of team
Semantic Infrastructure Dimensions StructurePeople: Location of Team

  • KM/KA Dept. – Cross Organizational, Interdisciplinary

  • Balance of dedicated and virtual, partners

    • Library, Training, IT, HR, Corporate Communication

  • Balance of central and distributed

  • Industry variation

    • Pharmaceutical – dedicated department, major place in the organization

    • Insurance – Small central group with partners

    • Beans – a librarian and part time functions

  • Which design – knowledge architecture audit


Semantic infrastructure dimensions technology infrastructure
Semantic Infrastructure Dimensions StructureTechnology Infrastructure

  • Enterprise platforms: from creation to retrieval to application

    • Semantic Infrastructure as the computer network

      • Applications – integrated meaning, not just data

  • Semantic Structure

    • Text Analytics – taxonomy, categorization, extraction

  • Integration Platforms – Content management, Search

    • Add structure to content at publication

    • Add structure to content at consumption


Infrastructure solutions resources technology
Infrastructure Solutions: Resources StructureTechnology

  • Text Mining

    • Both a structure technology – taxonomy development

    • And an application

  • Search Based Applications

    • Portals, collaboration, business intelligence, CRM

    • Semantics add intelligence to individual applications

    • Semantics add ability to communicate between applications

  • Creation – content management, innovation, communities of practice (CoPs)

    • When, who, how, and how much structure to add

    • Workflow with meaning, distributed subject matter experts (SMEs) and centralized teams


Infrastructure solutions elements business processes
Infrastructure Solutions: Elements StructureBusiness Processes

  • Platform for variety of information behaviors & needs

    • Research, administration, technical support, etc.

    • Types of content, questions

  • Subject Matter Experts – Info Structure Amateurs

  • Web Analytics – Feedback for maintenance & refine

  • Enhance Basic Processes – Integrated Workflow

    • Enhance Both Efficiency and Quality

  • Enhance support processes – education, training

  • Develop new processes and capabilities

    • External Content – Text mining, smarter categorization


Semantic infrastructure the start and foundation knowledge architecture audit
Semantic Infrastructure: The start and foundation StructureKnowledge Architecture Audit

  • Knowledge Map - Understand what you have, what you are, what you want

    • The foundation of the foundation

  • Contextual interviews, content analysis, surveys, focus groups, ethnographic studies, Text Mining

  • Category modeling – “Intertwingledness” -learning new categories influenced by other, related categories

  • Natural level categories mapped to communities, activities

    • Novice prefer higher levels

    • Balance of informative and distinctiveness

  • Living, breathing, evolving foundation is the goal


  • Semantic infrastructure the start and foundation knowledge architecture audit1
    Semantic Infrastructure: The start and foundation StructureKnowledge Architecture Audit

    • Phase I

      • Initial Discussion, Plan

      • Get high level structure, inventory of content

      • Get high level business, organization, technology structure

    • Onsite – 1 day to 1 week

      • Planning meetings, general contextual info

      • Get access to content – documents, databases, spider

      • Decide who to talk to and get access to them


    Semantic infrastructure the start and foundation knowledge architecture audit2
    Semantic Infrastructure: The start and foundation StructureKnowledge Architecture Audit

    • Phase II

      • Spider Content

      • Explore content – text mining, clusters, categorization, etc.

      • Work sessions – SME’s, feedback in initial structures

      • Interviews – SME’s – work flow, info in business processes

      • Survey – optional – broad look at interview info

    • Phase III

      • Develop K Map – ontologies, taxonomies, categorization

      • Train K Map – questions, feedback

      • Develop Expertise Map, Other Maps // Train

    • Final Strategy Report and K Map


    Knowledge architecture audit knowledge map
    Knowledge Architecture Audit: StructureKnowledge Map


    Semantic infrastructure enterprise taxonomies wrong approach
    Semantic Infrastructure StructureEnterprise Taxonomies: Wrong Approach

    • Very difficult to develop - $100,000’s

    • Even more difficult to apply

      • Teams of Librarians or Authors/SME’s

      • Cost versus Quality

    • Problems with maintenance

    • Cost rises in proportion with granularity

    • Difficulty of representing user perspective

    • Social media requires a framework – doesn’t create one

      • Tyranny of the majority, madness of crowds


    Semantic infrastructure content structures new approach
    Semantic Infrastructure StructureContent Structures: New Approach

    • Simple Subject Taxonomy structure

      • Easy to develop and maintain

    • Combined with categorization capabilities

      • Added power and intelligence

    • Combined with Faceted Metadata

      • Dynamic selection of simple categories

      • Allow multiple user perspectives

        • Can’t predict all the ways people think

        • Monkey, Banana, Panda

    • Combined with ontologies and semantic data

      • Multiple applications – Text mining to Search

      • Combine search and browse


    Semantic infrastructure design people technology business processes
    Semantic Infrastructure Design: StructurePeople, Technology, Business Processes

    • People (Central) – tagging, evaluating tags, fine tune rules and taxonomy

    • People (Users) - social tagging, suggestions

    • Software - Text analytics, auto-categorization, entity extraction

    • Software – Search, Content Management, Portals-Intranets

      • Hybrid model – combination of automatic and human

    • Business Processes – integrated search with activities, text analytics based applications , intelligent routing


    Semantic infrastructure benefits why semantic infrastructure
    Semantic Infrastructure Benefits StructureWhy Semantic Infrastructure

    • Unstructured content = 80% or more of all content

    • Limited Usefullness – database of unstructured content

    • Need to add (infra) structure to make it useful

    • Information is about meaning, semantics

    • Search is about semantics, not technology

    • Can’t Google do it?

      • Link Algorithm – human act of meaning

      • Doesn’t work in enterprise

      • 1,000’s of editors adding meaning

    • New technology makes it possible – Text Analytics


    Semantic infrastructure benefits general time and productivity
    Semantic Infrastructure Benefits StructureGeneral Time and Productivity

    • Time Savings – Too Big to Believe?

      • Lost time searching - $12M a year per 1,000

      • Cost of recreating lost information - $4.5M per 1,000

      • Cost of not finding the right information – Years?

      • 10% improvement = $1.2M a year per 10,000

    • Making Metrics Human

      • Number of addition FTE’s at no cost (enhanced productivity)

      • Savings passed on to clients

      • Spreadsheet of extra activities (ex. Training – working smarter

      • Build a more integrated, smarter organization


    Semantic infrastructure benefits return on existing technology
    Semantic Infrastructure Benefits StructureReturn on Existing Technology

    • Enterprise Content Management - $100K - $2M

      • Underperforming – year after year, new initiative every 5 years

    • ECM as part of a Platform

      • Enhance search – improved metadata, especially keywords

    • A Hybrid Model of ECM and Metadata

      • Authors, editors-librarians, Text Analytics

      • Submit a document -> TA generates metadata, extracts concepts, Suggests categorization (keywords) -> author OK’s (easy task) -> librarian monitors for issues

      • Use results as input into analytics


    Semantic infrastructure benefits return on existing technology1
    Semantic Infrastructure Benefits StructureReturn on Existing Technology

    • Enterprise Search - $100K - $2M

      • Cost Effective and good quality keywords / categorization

      • More metadata – faceted navigation

    • Work with ECM or dynamically generate categorization at search results time

    • Rich results – summaries, categorization, facets like date, people, organizations, etc. Tag clouds and related topics

    • Foundation for Search Based Applications – all need semantics


    Semantic infrastructure benefits infrastructure vs projects
    Semantic Infrastructure Benefits StructureInfrastructure vs. Projects

    • Strategic foundation vs. Short Term

    • Integrated solution – CM and Search and Applications

      • Better results

      • Avoid duplication

    • Semantics

      • Small comparative cost

      • Needed to get full value from all the above

    • ROI – asking the wrong question

      • What is ROI for having an HR department?

      • What is ROI for organizing your company?


    Semantic infrastructure benefits knowledge management benefits
    Semantic Infrastructure Benefits StructureKnowledge Management Benefits

    • Foundation for advanced knowledge representations

      • Capture the depth and complexity of knowledge context

    • Connect KM initiatives to entire organization

      • Information AND Knowledge (and Data)

      • CIO resources with KM depth

    • Foundation for KM initiatives that work and deliver value

      • Portals and Expertise and Communities

    • New KM initiatives – combine sophisticated handling of language and knowledge and education

    • Return knowledge to knowledge management

      • Cognitive Science could change everything (almost)


    Semantic infrastructure benefits selling the benefits
    Semantic Infrastructure Benefits StructureSelling the Benefits

    • CTO, CFO, CEO

      • Doesn’t understand – wrong language

      • Semantics is extra – harder work will overcome

      • Not business critical

      • Not tangible – accounting bias

      • Does not believe the numbers

      • Believes he/she can do it

    • Need stories and figures that will connect

    • Need to understand their world – every case is different

    • Need to educate them – Semantics is tough and needed


    Conclusion
    Conclusion Structure

    • Semantic Infrastructure is not just a project

      • Foundation and Platform for multiple projects

    • Semantic Infrastructure is not just about search

      • It is about language, cognition, and applied intelligence

    • Strategic Vision (articulated by K Map) is essential

      • Even for your under the radar vocabulary project

      • Paying attention to theory is practical

    • Benefits are enormous – believe it!

    • Think Big, Start Small, Scale Fast

      • Initial Project = +10%, All Other Projects = -50%


    Questions

    Questions? Structure

    Tom Reamytomr@kapsgroup.com

    KAPS Group

    Knowledge Architecture Professional Services

    http://www.kapsgroup.com