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Knowledge Sharing and Reuse in IBROW

Knowledge Sharing and Reuse in IBROW. Baseline Libraries and Web Technology. Contents of the Talk. KMI Baseline Library Contents, Organization, Use and Reuse Tool Support for browsing/editing library components Web-Onto, Tadzebao

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Knowledge Sharing and Reuse in IBROW

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  1. Knowledge Sharing and Reuse in IBROW Baseline Libraries and Web Technology

  2. Contents of the Talk • KMI Baseline Library • Contents, Organization, Use and Reuse • Tool Support for browsing/editing library components • Web-Onto, Tadzebao • Tool Support for interoperating with the library over the web • KMI Lisp Web Server • KA Support for using the library over the web • Internet Reasoning System

  3. KMI Baseline Library

  4. Components of Knowledge Sharing • Epistemological Framework • UPML Architecture, TMDA • Modelling Language • UPML, OCML • Libraries • KMI Library of Problem Solving Components • Interoperability Support • CORBA, Lisp Server • KA Support • IBROW Broker, IRS

  5. Problem Solving Methods Domains Organization of the Library Problem Types Parametric Design Propose&Revise KMI Office Allocation KMI Office Allocation as parametric design solved by Propose&Revise Applications Base Ontology

  6. Features of the Library • Organization driven by generic problem type • Parametric Design, Classification, etc.. • Use of different types of formal ontologies • Task, method, domain, application, base ontology • Notions of Tasks and PSMs are part of the base ontology • Supports different approaches to PSM modelling • Based on the OCML modelling language • Operational components • Runs on several common lisp environments

  7. Use of the Library • Office Allocation • Sisyphus1, KMI Office Allocation • Elevator Configuration • VT • Engineering Design • sliding bearing design, truck cab design, casting technology design • Knowledge Management • Planet-Onto, BAE-Workbook • Health-care • HC-ReMa, PatMan, Rich-ODL projects • Classification • RockyIII

  8. Here is the truck...

  9. Success story but..... • Reuse only for power users • High entry costs • No tool support for reuse • Reuse only through “dive-in process” • No support for interoperability • Straightforward reuse only within lisp images

  10. Lowering Entry Costs • Web-based browsing, editing and visualization support • Web-Onto, Tadzebao tools • Access through the web • KMI Web Lisp Server • Addressing non-power-users • KMI Internet Reasoning Service

  11. Web-Onto & Tadzebao

  12. Web-Onto Snapshot of HC-ReMa Medical Ontology

  13. Web-Onto and Tadzebao: Main Points • Support for web-based editing and browsing of ontologies • Platform-Independent • Integration of Knowledge Modelling (OCML) with Groupware (Tadzebao) • Automatic generation of Oracle DB schemata for end-user application delivery

  14. KMI Internet Reasoning Service

  15. KMI Internet Reasoning Service • Builds on KMI Modelling and Internet Technology • Uses library, OCML, Web-Onto, Lisp Web Server • Puts the library on the web “for real” • From browsing to execution • Aims to support different types of reuse • Direct reuse (very low reuse costs) • Parametric reuse (low reuse costs) • Plug&Play • Manual (power users) • IBROW broker

  16. Problem Solving Methods Domain Simple Direct-Reuse Scenario Problem Types Classification Simple-classifier Apples Minerals Apple Classification Minearal Classification Applications Base Ontology

  17. Define Classification Task Ontology class classification-task relation best-match relation class-has-match-score class standard-class-instance-match-score relation better-match-score rule standard-match-score-comparison function the-better-match-score relation has-feature function feature-value class standard-feature-score class observables

  18. Simple Classification PSM

  19. Off-the-shelf domains • Apples (from Amsterdam) • Minerals (from Spain)

  20. Conclusions • KMI Library now a well established resource • Modelling, epistemological issues under control. KA issues are emerging as the important ones • Technology itself is reusable • E.g., Knowledge Management, Information Retrieval

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