Km World Taxonomy Boot Camp 2011

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Presentation on Taxonomies and Ontology\'s for Enterprise Search (Includes 3 case study examples)

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  • Business and IT savings will be captured when we write business cases.
  • Business and IT savings will be captured when we write business cases.
  • Business and IT savings will be captured when we write business cases.
  • Business and IT savings will be captured when we write business cases.
  • Business and IT savings will be captured when we write business cases.
  • Business and IT savings will be captured when we write business cases.
  • Business and IT savings will be captured when we write business cases.
  • Business and IT savings will be captured when we write business cases.
  • Business and IT savings will be captured when we write business cases.
  • Business and IT savings will be captured when we write business cases.
  • Business and IT savings will be captured when we write business cases.
  • Business and IT savings will be captured when we write business cases.
  • Business and IT savings will be captured when we write business cases.
  • Business and IT savings will be captured when we write business cases.
  • Business and IT savings will be captured when we write business cases.
  • Km World Taxonomy Boot Camp 2011

    1. 1. Designing and Implementing Taxonomies and Ontology's in Enterprise Search KM World Taxonomy Boot Camp - 2011
    2. 2. Overview <ul><li>Overview: looking at how several organizations use taxonomies and ontology's to improve unstructured content search and retrieval and meet the business expectations of the KM solution </li></ul>
    3. 3. Objectives <ul><li>This presentation will focus on the design and implementation of taxonomies and ontology's to improve unstructured content search and retrieval. Specifically this presentation will take a look at several organizations and how the approach to enterprise search enables a successful search result. Along with presenting examples of taxonomy adoption an underlying view of the content types and metadata will be presented that met the business expectations of the KM solution. </li></ul>
    4. 4. Agenda <ul><li>Taxonomy and Ontology </li></ul><ul><li>Information Model </li></ul><ul><li>Unstructured Data </li></ul><ul><li>Content Types and Metadata </li></ul><ul><li>Search Engines </li></ul><ul><ul><li>Microsoft Fast </li></ul></ul><ul><ul><li>Google Search Appliance </li></ul></ul><ul><li>Case Studies </li></ul><ul><ul><li>Military Organization </li></ul></ul><ul><ul><li>Retail Organization </li></ul></ul><ul><ul><li>Financial Organization </li></ul></ul>
    5. 5. Taxonomies and Ontology's <ul><li>Taxonomy: the science or technique of classification; a classification into ordered categories; example a taxonomy of animals. </li></ul>Taxonomies and Ontology's are a way of classifying something Ontology: ontology deals with questions concerning what entities exist or can be said to exist, and how such entities can be grouped, related within a hierarchy, and subdivided according to similarities and differences; example a ontology of a car.
    6. 6. Information Model (Facts) <ul><li>Information Model is typically developed from the Ontology </li></ul><ul><li>Business Rules around the information relationships are established </li></ul><ul><li>The Business Rules contributed to the construction of the information model </li></ul><ul><li>The information represents a sharable, stable, and organized structure of information requirements for your Knowledge Management System (KMS) </li></ul><ul><li>Information Model supports the search process through establishing relationships between the content and describing how this information behaves </li></ul>
    7. 7. Information Model Example Source: CMBL Information Model - http://www.mod.uk/NR/rdonlyres/C176E21A-776C-46FA-AE2B-3CAD597CDD6A/0/CBML_information_model.pdf
    8. 8. Unstructured Data <ul><li>Unstructured Data – In contrast to structured data, unstructured data has no identifiable structure associated with it </li></ul><ul><li>Unstructured data comes in the form of: </li></ul><ul><ul><li>Images/Objects </li></ul></ul><ul><ul><li>Email </li></ul></ul><ul><ul><li>Documents (word, PDF, etc.) </li></ul></ul><ul><ul><li>Spreadsheets (i.e., excel) </li></ul></ul><ul><li>Most data in the enterprise today is in the form of unstructured data </li></ul><ul><li>Unstructured data contains the explicit knowledge of the enterprise and has to be made available to the knowledge management system </li></ul><ul><li>In order to catalog, search and retrieve unstructured data we must make it identifiable by building structure around it. </li></ul><ul><li>This structure comes in the form of Content Types and Metadata. </li></ul>
    9. 9. Content Types and Metadata <ul><li>Content Types – a reusable collection of metadata, and other settings for a category of artifacts, items, or documents </li></ul><ul><li>Content types enable you to manage the settings for a category of information in a centralized and reusable way </li></ul><ul><li>Content Types encapsulate data requirements </li></ul><ul><li>Content Types enable Content Standardization and are File Format Independent </li></ul><ul><li>Metadata – The metadata represents the properties of a Content Type </li></ul>
    10. 10. Search Engines <ul><li>Microsoft FAST for SharePoint Provided: </li></ul><ul><li>Directly index against the content </li></ul><ul><li>Advance Filtering </li></ul><ul><li>Navigation breadcrumbs </li></ul><ul><li>Unsupervised clustering </li></ul><ul><li>Concept Extraction </li></ul><ul><ul><li>Google Search Appliance (GSA) Provided: </li></ul></ul><ul><li>Dynamic Scalability - Scale to millions of documents/artifacts </li></ul><ul><li>Fine tune relevancy - Ranking Framework, Node Biasing, and Collection Biasing </li></ul><ul><li>Customizable security, enabling early binding and late binding </li></ul><ul><li>Social search features, including 'User Added Results' </li></ul><ul><li>User-centric innovations such as Query Suggestions </li></ul><ul><li>Enhanced search quality with improved precision </li></ul>The Following Case Studies utilized either Microsoft SharePoint Search, Microsoft Fast for SharePoint or Google Search Appliance (GSA):
    11. 11. Case Study – Military Organization <ul><li>Opportunity: Capture of Tacit and Explicit Knowledge (retiring and rotational workforce) and rules in response to Defense Base Closure and Realignment (BRAC) Commission movements </li></ul><ul><li>Activities: </li></ul><ul><ul><li>Knowledge Capture </li></ul></ul><ul><ul><li>Create Knowledge Repository </li></ul></ul><ul><ul><li>Implement Enterprise Search </li></ul></ul><ul><li>Results: </li></ul><ul><ul><li>Knowledge Identified/Cataloged (Key Knowledge Loss Avoided) </li></ul></ul><ul><ul><li>Utilized Taxonomy to Structure the Site and Categorize the Content </li></ul></ul><ul><ul><li>Utilized Ontology/Information Model to establish information relationships and contribute to search engine optimization </li></ul></ul>
    12. 12. Case Study – Military Organization – Taxonomy/Content Structure <ul><li>Taxonomy: </li></ul><ul><li>Provided infrastructure to deliver Site and Content structure </li></ul>Taxonomy Structure Directorate -- Division ---- Groups ------ Battalions Content Structure within the Taxonomy /SOP /Training /Projects /Plans /General Admin /Policy and Procedures
    13. 13. Case Study – Military Organization – Site Structure (1)
    14. 14. Case Study – Military Organization – Site Structure (2)
    15. 15. Case Study – Military Organization – Ontology/Info Model Ontology/Information Model: Capture the information relationships and contribute to Search Engine Optimization Personnel Directorate Division System Battalions Groups Readiness & Mobilization Commands 1 or More Support Operations Support Operations Support Operations Support Operations Commands 1 or More Commands 1 or More Is a Kind of Is a Kind of Role Performs duties within Performs duties within Performs duties within Performs duties within Chief of Staff Commanding General BRAC POC Director Sealift Operations Is a Kind of Is a Kind of Is a Kind of Is a Kind of
    16. 16. Case Study – Military Organization - Search <ul><li>Search decision - Recommended the Use of Google Search Appliance (GSA) to Provide: </li></ul><ul><ul><li>Dynamic Scalability </li></ul></ul><ul><ul><li>Fine Tune Relevancy </li></ul></ul><ul><ul><li>Customizable Security </li></ul></ul><ul><ul><li>Social Search Features </li></ul></ul><ul><ul><li>User-centric functionality </li></ul></ul><ul><ul><li>Enhanced Search Quality </li></ul></ul><ul><li>However; initial implementation utilized SharePoint out-of-the-box search capabilities with future enhancements to consider GSA or Microsoft Fast. </li></ul>
    17. 17. Case Study – Retail Organization <ul><li>Opportunity: Capture of Tacit and Explicit Knowledge of Vendors and make this knowledge available to associates. Lessen the need for company SME’s and enable vendor knowledge transfer. </li></ul><ul><li>Activities: </li></ul><ul><ul><li>Development of Taxonomy; Information Model; and Content Types/Metadata </li></ul></ul><ul><ul><li>Performed Vendor Knowledge Capture </li></ul></ul><ul><ul><li>Create Knowledge Repository </li></ul></ul><ul><li>Results: </li></ul><ul><ul><li>Knowledge Identified/Cataloged (Key Vendor assets Captured) </li></ul></ul><ul><ul><li>Established a standardized processes for capturing, storing, and searching intellectual assets </li></ul></ul><ul><ul><li>Software Project Ramp up time decreased </li></ul></ul><ul><ul><li>Improved utilization of SME’s </li></ul></ul>
    18. 18. Case Study – Retail Organization – Taxonomy
    19. 19. Case Study – Retail Organization – Site Structure Organizational Taxonomy Organizational (level 2) Taxonomy
    20. 20. Case Study – Retail Organization – Ontology/Info Model <ul><li>Results: </li></ul><ul><ul><li>Knowledge Identified/Cataloged (Vendor Knowledge Cataloged) </li></ul></ul><ul><ul><li>Architecture will aid in fulfilling search requirements </li></ul></ul><ul><ul><li>Established Rules and Policies concerning information </li></ul></ul>
    21. 21. Case Study – Retail Organization – Content Types/Metadata Content Types/Metadata: Will aid in the storing, and searching of Intellectual assets Content Type: Company Artifact Metadata Fields: Artifact Category Artifact Contact Confidentiality Level (Shared, Controlled, or Restricted) Summary Language Search Keywords Country Division Content Type: ISDLC Artifact Metadata Fields: Artifact Type Project Id
    22. 22. Case Study – Retail Organization - Search <ul><li>Search decision - utilized SharePoint out-of-the-box search capabilities </li></ul><ul><li>Although the initial implementation utilized SharePoint out-of-the-box search capabilities; future enhancements will implement Microsoft Fast for search. To provide the following search functionality: </li></ul><ul><ul><ul><li>Directly index against the content </li></ul></ul></ul><ul><ul><ul><li>Advance Filtering </li></ul></ul></ul><ul><ul><ul><li>Navigation breadcrumbs </li></ul></ul></ul>
    23. 23. Case Study – Financial Organization <ul><li>Opportunity: Transition, Capture and Catalog Tacit and Explicit Knowledge from across several business units and produce content that is solution base, fast and easily searchable and retrievable. </li></ul><ul><li>Activities: </li></ul><ul><ul><li>Provide Content Management </li></ul></ul><ul><ul><li>Provide Business Process Integration with Workflows </li></ul></ul><ul><ul><li>Establish Enterprise Search </li></ul></ul><ul><ul><li>Provide Admin and Business Intelligence Capabilities </li></ul></ul><ul><li>Results: </li></ul><ul><ul><li>Knowledge Identified/Cataloged (Content Structured and Migrated) </li></ul></ul><ul><ul><li>Enterprise Search Enabled (Producing Solution Based Results) </li></ul></ul><ul><ul><li>Knowledge Portal Completed with BI, and Workflows Implemented </li></ul></ul>
    24. 24. Content Type & Metadata Structure MS Share Point 2010 Platform KM Search Flow & Display Work Flow (Operational & Governance) Present Content Business Taxonomy Migration Ready Content Reporting System Add – On (As Needed) KM Enterprise Solution Case Study – Financial Organization – KM Framework
    25. 25. Case Study – Financial Organization - Taxonomy <ul><li>Taxonomy: Provided logical Site Structure and Content Structure for capturing and cataloging content for search. </li></ul>
    26. 26. Case Study – Financial Organization – Site Structure (1)
    27. 27. Case Study – Financial Organization – Site Structure (2)
    28. 28. Case Study – Financial Organization – Ontology/Info Model <ul><li>Ontology/Information Model: Capture the information relationships and contribute to Search Engine Optimization </li></ul>
    29. 29. Case Study – Financial Organization – Content Types/Metadata Content Type Structure for Page Layout to capture web based Content
    30. 30. Case Study – Financial Organization – Content Types/Metadata Content Type Structure for Documents to capture document (PDF, Excel, Word, etc.) based Content
    31. 31. Case Study – Financial Organization - Search <ul><li>Search decision - Utilized Microsoft Fast for SharePoint </li></ul><ul><li>Microsoft Fast for SharePoint provided the following search functionality: </li></ul><ul><ul><ul><li>Directly index against the content </li></ul></ul></ul><ul><ul><ul><li>Advance Filtering </li></ul></ul></ul><ul><ul><ul><li>Navigation breadcrumbs </li></ul></ul></ul><ul><ul><ul><li>Unsupervised clustering </li></ul></ul></ul><ul><ul><ul><li>Concept Extraction </li></ul></ul></ul>
    32. 32. Designing Taxonomies and Ontology's for Enterprise Search
    33. 33. Designing Taxonomies and Ontology's for Enterprise Search A.J. Rhem & Associates, Inc. 500 North Michigan Ave., Suite 300 Chicago, Illinois 60611 Phone: 312-396-4024 email: [email_address] Website: www.ajrhem.com

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