Advertisement

Using a Well-Founded Multi-level Theory to Support the Analysis and Representation of the Powertype Pattern in Conceptual Modeling

  • Victorio Albani CarvalhoEmail author
  • João Paulo A. Almeida
  • Giancarlo Guizzardi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9694)

Abstract

Multi-level conceptual modeling addresses the representation of subject domains dealing with multiple classification levels. In such domains, the occurrence of situations in which instances of a type are specializations of another type is recurrent. This recurrent phenomenon is known in the conceptual modeling community as the powertype pattern. The relevance of the powertype pattern has led to its adoption in many important modeling initiatives, including the UML. To address the challenge of multi-level modeling, we have proposed an axiomatic well-founded theory called MLT. In this paper, we demonstrate how MLT can be used as a reference theory for capturing a number of nuances related to the modeling of the powertype pattern in conceptual modeling. Moreover, we show how this theory can be used to analyze, expose limitations and redesign the UML support for modeling this pattern.

Keywords

Conceptual modeling Multi-level modeling Powertype UML 

Notes

Acknowledgments

This research is funded by the Brazilian Research Funding Agencies CNPq (grants number 311313/2014-0, 485368/2013-7, 312158/2015-7 and 461777/2014-2) and CAPES. The authors would like to thank Claudenir M. Fonseca for implementing the Visual Paradigm plugin for the UML profile presented here.

References

  1. 1.
    Halpin, T., Morgan, T.: Information Modeling and Relational Databases. Morgan Kaufmann, San Francisco (2008)Google Scholar
  2. 2.
    Recker, J., Rosemann, M., Green, P., Indulska, M.: Do ontological deficiencies in modeling grammars matter? MIS Q. 35(1), 57–79 (2011)Google Scholar
  3. 3.
    Guizzardi, G.: Ontological foundations for structural conceptual models. University of Twente, Enschede, The Netherlands (2005)Google Scholar
  4. 4.
    Mayr, E.: The Growth of Biological Thought: Diversity, Evolution, and Inheritance. Belknap Press, Cambridge (1982)‬‬‬Google Scholar
  5. 5.
    Neumayr, B., Grün, K., Schrefl, M.: Multi-level domain modeling with m-objects and m-relationships. In: Proceedings of the 6th Asia-Pacific Conference on Conceptual Modeling, pp. 107–116 (2009)Google Scholar
  6. 6.
    Atkinson, C., Kühne, T.: The essence of multilevel modeling. In: Proceedings of the 4th International Conference on the Unified Modeling Language, pp. 19–33, Toronto, Canada (2001)Google Scholar
  7. 7.
    Gonzalez-Perez, C., Henderson-Sellers, B.: A powertype-based metamodelling framework. Softw. Syst. Model. 5(1), 72–90 (2006)CrossRefGoogle Scholar
  8. 8.
    Odell, J.: Powertypes. J. Object-Oriented Program. 7(2), 8–12 (1994)MathSciNetGoogle Scholar
  9. 9.
    Cardelli, L.: Structural subtyping and the notion of powertype. In: Proceedings of the 15th ACM Symposium of Principles of Programming Languages, pp. 70–79 (1988)Google Scholar
  10. 10.
    ISO/IEC: ISO/IEC 24744: Software Engineering – Metamodel for Development Methodologies. ISO, Geneva (2007)Google Scholar
  11. 11.
    Fowler, M.: Analysis Patterns: Reusable Object Models. Addison-Wesley, Boston (1997)Google Scholar
  12. 12.
    OMG: UML Superstructure Specification – Version 2.4.1 (2011)Google Scholar
  13. 13.
    Carvalho, V.A., Almeida, J.P.A.: Towards a Well-Founded Theory for Multi-level Conceptual Modeling (2015, submitted). http://nemo.inf.ufes.br/mlt
  14. 14.
    Carvalho, V.A., Almeida, J.P.A.: A semantic foundation for organizational structures: a multi-level approach. In: 19th IEEE International Enterprise Distributed Object Computing Conference (EDOC 2015), pp. 50–59, Adelaide, Australia (2015)Google Scholar
  15. 15.
    Carvalho, V.A., Almeida, J.P.A., Fonseca, C.M., Guizzardi, G.: Extending the foundations of ontology-based conceptual modeling with a multi-level theory. In: Johannesson, P., et al. (eds.) ER 2015. LNCS, vol. 9381, pp. 119–133. Springer, Heidelberg (2015). doi: 10.1007/978-3-319-25264-3_9 CrossRefGoogle Scholar
  16. 16.
    Guizzardi, G., et al.: Towards ontological foundation for conceptual modeling: the unified foundational ontology (UFO) story. Appl. Ontol. 10, 259–271 (2015). IOS PressCrossRefGoogle Scholar
  17. 17.
    Atkinson, C., Kühne, T.: Meta-level independent modeling. In: International Workshop on Model Engineering (in conjunction with ECOOP 2000), Cannes, France (2000)Google Scholar
  18. 18.
    Atkinson, C., Kühne, T.: Reducing accidental complexity in domain models. Softw. Syst. Model. 7(3), 345–359 (2008). SpringerCrossRefGoogle Scholar
  19. 19.
    Jeusfeld, M.A.: Metamodeling and method engineering with conceptbase. In: Jeusfeld, M.A., Jarke, M., Mylopoulos, J. (eds.) Metamodeling for Method Engineering, pp. 89–168. MIT Press, Cambridge (2009)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Victorio Albani Carvalho
    • 1
    • 2
    Email author
  • João Paulo A. Almeida
    • 1
  • Giancarlo Guizzardi
    • 1
  1. 1.Ontology and Conceptual Modeling Research Group (NEMO)Federal University of Espírito Santo (UFES)VitóriaBrazil
  2. 2.Federal Institute of Espírito Santo (IFES)ColatinaBrazil

Personalised recommendations