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Developing Ontologies for Collaborative Engineering in Mechatronics

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4th ESWC 2007, Innsbruck, Austria

4th ESWC 2007, Innsbruck, Austria

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    • 1. Developing Ontologies for Collaborative Engineering in Mechatronics Violeta Damjanović, Wernher Behrendt, Manuela Plößnig and Merlin Holzapfel Salzburg Research, Salzburg, Austria 4th ESWC 2007, Innsbruck, Austria
    • 2. Generic Mechatronic Product
    • 3. Mechatronic Domain
    • 4. ImportNET Ontology Landscape
    • 5.
      • Collaborative Engineering
        • Application integration; Knowledge integration; Process integration
      • Mechatronic Engineering
        • Thramboulidis’ metamodel of Integrated Mechatronics – Mechatronic processes
        • Yoshioka’ knowledge structure for the Knowledge Intensive Engineering Framework (KIEF) – Mechatronic artefacts
      • Mechatronic Domain Modeling
        • e.g. FBA (Functional Block Adapter) stereotype
        • STEP (Standard for Exchange Product Data)
      Research Issues in ImportNET
    • 6.
      • ImportNET Approach to Mechatronic Domain Modeling
        • Ontology Landscape in ImportNET
        • Methodology for the development of the Mechatronic Ontology
        • Ontology Alignment to the DOLCE F oundational Ontology
      Key Ideas
    • 7. Ontology Development Methodologies – Methontology
      • Methontology
        • Glossary of terms
        • concept taxonomies
        • ad-hoc binary relation diagrams
        • concept dictionary
        • it describes: relations; instance attributes; class attributes; constants; formal axioms; rules; instances
      • Methontology is agnostic about the target ontology representation language
    • 8. Ontology Development Methodologies – DILIGENT
      • DILIGENT
        • addresses collaborative development of an ontology
      • DILIGENT steps
        • BUILD – creates an initial, incomplete ontology
        • LOCAL ADAPTATION – specific groups can have their variant of the ontology
        • ANALYSIS – of the local ontologies
        • REVISE – re-alignment of the shared ontology with the local ones
        • UNDERSTAND the shared ontology
        • IDENTIFY SIMILARITIES – between local and shared ontology
      • DILIGENT is agnostic about the target ontology representation language
    • 9. Ontology Development Methodologies – On-To-Knowledge (OTK)
      • OTK is a high level methodology
        • Kickoff
        • Refinement
          • gather a seed taxonomy
          • develop a seed ontology
          • conceptualisation and formalisation
          • tool-supported refinement
        • Evaluation
        • Maintenance
      • OTK is agnostic about the target ontology representation language
    • 10. Ontology Development Methodologies – DynamOnt
      • DynamOnt
        • Identify the problem; Structure the problem;
        • Identify concrete purpose and scenarios;
        • Identify main concepts of domain matter;
        • Create non-formal methods;
        • Knowledge design; Community design; Software design;
        • Implementation
      • DynamOnt is dedicated to uses DOLCE as the target ontology representation language.
      • DynamOnt uses DOLCE ontology design patterns
    • 11. DOLCE – A Foundational and Formal Ontology
      • Descriptive
      • Ontology for
      • Linguistic and
      • Cognitive
      • Engineering
          • developed in the WonderWeb project
    • 12.
        • Participation pattern
        • Description-Situation pattern
        • Role-Task pattern
        • Design-Artifact pattern
        • Agent-Activity pattern
        • Information-Object pattern
      DynamOnt Ontology Patterns
    • 13. Description and Situation Pattern
    • 14. Ontology Landscape and Its Alignment to DOLCE
    • 15. Current Work – Modeling the Mechatronic Life-Cycle
      • In engineering the V-model defines a generic life-cycle model
      • Methodology
        • Top layer of the V-model in DOLCE
        • Analyse the actual life-cycle models using Event Process Chain (EPC) notation (a semi-formal modeling language)
        • Translate the EPC diagrams into the task ontology of DOLCE
    • 16. Mechatronic Engineering Lifecycle A
    • 17. Top Layer of the V-Model A
    • 18. EPC to Express V-Model A
    • 19. Life-Cycle Model Ontology – Layers of Specificity A
    • 20. Summary and Conclusion
      • ImportNET is trying to bring the Semantic Web technologies to mechatronic engineering
      • Mechatronic engineering is multi disciplinary and therefore needs multiple ontologies
      • The engineering process needs process modeling
      • The engineering artifacts need structural modeling
      • Therefore our ontologies need to capture the dynamic and the static aspects of the domains
    • 21.
      • Thank you !
      • Questions ?
      • Contact :
        • violeta.damjanovic @ salzburgresearch.at
        • http://www.salzburgresearch.at