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Ontology-Based Metamodeling

  • Knut Hinkelmann
  • Emanuele Laurenzi
  • Andreas Martin
  • Barbara Thönssen
Chapter
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 141)

Abstract

Decision makers use models to understand and analyze a situation, to compare alternatives and to find solutions. Additionally, there are systems that support decision makers through data analysis, calculation or simulation. Typically, modeling languages for humans and machine are different from each other. While humans prefer graphical or textual models, machine-interpretable models have to be represented in a formal language. This chapter describes an approach to modeling that is both cognitively adequate for humans and processable by machines. In addition, the approach supports the creation and adaptation of domain-specific modeling languages. A metamodel which is represented as a formal ontology determines the semantics of the modeling language. To create a graphical modeling language, a graphical notation can be added for each class of the ontology. Every time a new modeling element is created during modeling, an instance for the corresponding class is created in the ontology. Thus, models for humans and machines are based on the same internal representation.

Keywords

Modeling Ontologies Metamodel Enterprise modeling Domain-specific modeling language 

Notes

Acknowledgements

This research has received funding from the European Community’s Framework Programme for Research and Innovation HORIZON 2020 (ICT-07-2014) under grant agreement number 644690 (CloudSocket).

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Knut Hinkelmann
    • 1
  • Emanuele Laurenzi
    • 1
  • Andreas Martin
    • 1
  • Barbara Thönssen
    • 1
  1. 1.School of BusinessFHNW University of Applied Sciences and Arts Northwestern SwitzerlandOltenSwitzerland

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