Developing Ontologies for Collaborative Engineering in Mechatronics
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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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Developing Ontologies for Collaborative Engineering in Mechatronics Developing Ontologies for Collaborative Engineering in Mechatronics Presentation Transcript

  • 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
  • Generic Mechatronic Product
  • Mechatronic Domain
  • ImportNET Ontology Landscape
    • 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
    • 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
  • 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
  • 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
  • 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
  • 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
  • DOLCE – A Foundational and Formal Ontology
    • Descriptive
    • Ontology for
    • Linguistic and
    • Cognitive
    • Engineering
        • developed in the WonderWeb project
      • Participation pattern
      • Description-Situation pattern
      • Role-Task pattern
      • Design-Artifact pattern
      • Agent-Activity pattern
      • Information-Object pattern
    DynamOnt Ontology Patterns
  • Description and Situation Pattern
  • Ontology Landscape and Its Alignment to DOLCE
  • 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
  • Mechatronic Engineering Lifecycle A
  • Top Layer of the V-Model A
  • EPC to Express V-Model A
  • Life-Cycle Model Ontology – Layers of Specificity A
  • 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
    • Thank you !
    • Questions ?
    • Contact :
      • violeta.damjanovic @ salzburgresearch.at
      • http://www.salzburgresearch.at