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Huy Pham, Deborah Stacey, Rozita Dara School of Computer Science University of Guelph

A Practical Ontology-Driven Workflow Composition Framework. Huy Pham, Deborah Stacey, Rozita Dara School of Computer Science University of Guelph Guelph, Ontario, Canada. Quick Overview. A brief survey of ontology-driven approaches to workflow composition (ODWC)

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Huy Pham, Deborah Stacey, Rozita Dara School of Computer Science University of Guelph

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  1. A Practical Ontology-Driven Workflow Composition Framework HuyPham, Deborah Stacey, RozitaDara School of Computer Science University of Guelph Guelph, Ontario, Canada

  2. Quick Overview • A brief survey of ontology-driven approaches to workflow composition (ODWC) • Proposal: A more modular and reusable approach to planning-based ODWC Knowledge Engineering and Ontology Development 2011

  3. Intro and Motivation • Automated workflow composition • A great tool to help non-expert users to overcome the expertise gap • The task of finding a sequence of actions that accomplishes a given goal (i.e., planning) Knowledge Engineering and Ontology Development 2011

  4. Intro and Motivation • Real-world WF problems are often knowledge-intensive, and hence can benefit from an ontology-driven approach • Standardized semantics • Expressive • Reasoning services • Problem: Many existing approaches either don't use planning, or do it in less reusable and modular ways Knowledge Engineering and Ontology Development 2011

  5. Existing Approaches • Interactive Composition • E.g., Hlomani, et. al. • WFs are composed interactively using inputs from user • Provide assistance instead of design proposals • Template-based Composition • E.g., Morik, et. al. • WF designs are suggested from a pre-built library of successful WF built by experts • Cannot help in unseen cases • Planning-based • E.g., Bernstein, et. al. • WF designs are proposed by planning algorithms • Adhoc, less reusable Knowledge Engineering and Ontology Development 2011

  6. How About? • Potential Benefits: • Loose coupling --> Reduced complexity + Increased reusability • Reusable compositional knowledge Knowledge Engineering and Ontology Development 2011

  7. A case study • An intelligent student advisor: Helps university students select courses, taking into account: • Core requirements • Course prerequisites • Student objectives • Requirements for Course Selection knowledge • Reusable  Course selection knowledge must be modeled in an ontology • Modular  Kept separated from other knowledge • Rich & Effective  Capture and use of expert advices Knowledge Engineering and Ontology Development 2011

  8. Course Ontology Knowledge Engineering and Ontology Development 2011

  9. Course Objective Ontology Knowledge Engineering and Ontology Development 2011

  10. Planning Ontology Knowledge Engineering and Ontology Development 2011

  11. Discussion • What worked: • Course selection • What didn't: • More elegant way of soliciting user's objectives • More planning constraints • More details in: • Our other paper, "Practical Goal-based Reasoning in Ontology-Driven Applications" • Our website, http://ontology.socs.uoguelph.ca/ Knowledge Engineering and Ontology Development 2011

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