Experimentally Motivated Transformations for Intermodel Links Between Conceptual Models

  • Zubeida C. Khan
  • C. Maria KeetEmail author
  • Pablo R. Fillottrani
  • Karina Cenci
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9809)


Complex system development and information integration at the conceptual layer raises the requirement to be able to declare intermodel assertions between entities in models that may, or may not, be represented in the same modelling language. This is compounded by the fact that semantically equivalent notions may have been represented with a different element, such as an attribute or class. We first investigate such occurrences in six ICOM projects and 40 models with 33 schema matchings. While equivalence and subsumption are in the overwhelming majority, this extends mainly to different types of attributes, and therewith requiring non-1:1 mappings. We present a solution that bridges these semantic gaps. To facilitate implementation, the mappings and transformations are declared in ATL. This avails of a common, and logic-based, metamodel to aid verification of the links. This is currently being implemented as proof-of-concept in the ICOM tool.


Transformation Rule Object Type Automate Reasoner Cardinality Constraint Eclipse Modeling Framework 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work is based in part upon research supported by the National Research Foundation of South Africa (Project UID90041) and the Argentinean Ministry of Science and Technology.


  1. 1.
    Atzeni, P., Cappellari, P., Torlone, R., Bernstein, P.A., Gianforme, G.: Model-independent schema translation. VLDB J. 17(6), 1347–1370 (2008)CrossRefGoogle Scholar
  2. 2.
    Atzeni, P., Gianforme, G., Cappellari, P.: Data model descriptions and translation signatures in a multi-model framework. AMAI 63, 1–29 (2012)zbMATHMathSciNetGoogle Scholar
  3. 3.
    Baudry, B., Ghosh, S., Fleurey, F., France, R., Le Traon, Y., Mottu, J.M.: Barriers to systematic model transformation testing. Comm. ACM 53(6), 139–143 (2010)CrossRefGoogle Scholar
  4. 4.
    Grau, B.C., Parsia, B., Sirin, E.: Combining OWL ontologies using \(\varepsilon \)-connections. J. Web Sem. 4(1), 40–59 (2006)CrossRefGoogle Scholar
  5. 5.
    Falbo, R.A., Guizzardi, G., Gangemi, A., Presutti, V.: Ontology patterns: clarifying concepts and terminology. In: Proceedings of OSWP 2013 (2013)Google Scholar
  6. 6.
    Fillottrani, P.R., Keet, C.M.: Conceptual model interoperability: a metamodel-driven approach. In: Bikakis, A., Fodor, P., Roman, D. (eds.) RuleML 2014. LNCS, vol. 8620, pp. 52–66. Springer, Heidelberg (2014)Google Scholar
  7. 7.
    Fillottrani, P.R., Franconi, E., Tessaris, S.: The ICOM 3.0 intelligent conceptual modelling tool and methodology. Semant. Web J. 3(3), 293–306 (2012)Google Scholar
  8. 8.
    Fillottrani, P.R., Keet, C.M.: A design for coordinated and logics-mediated conceptual modelling. In: Proceedings of DL 2016, (in print). CEUR-WS, pp. 22–25, Cape Town, South Africa, April 2016Google Scholar
  9. 9.
    Ghidini, C., Serafini, L., Tessaris, S.: Complexity of reasoning with expressive ontology mappings. In: Proceedings of FOIS 2008, FAIA, vol. 183, pp. 151–163. IOS Press (2008)Google Scholar
  10. 10.
    Golas, U., Ehrig, H., Hermann, F.: Formal specification of model transformations by triple graph grammars with application conditions. Elect. Comm. EASST 39, 26 (2011)Google Scholar
  11. 11.
    Grønmo, R., Møller-Pedersen, B., Olsen, G.K.: Comparison of three model transformation languages. In: Paige, R.F., Hartman, A., Rensink, A. (eds.) ECMDA-FA 2009. LNCS, vol. 5562, pp. 2–17. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  12. 12.
    Jouault, F., Allilaire, F., Bzivin, J., Kurtev, I.: ATL: a model transformation tool. Sci. Comput. Program. 72(1–2), 31–39 (2008)CrossRefzbMATHMathSciNetGoogle Scholar
  13. 13.
    Keet, C.M., Fillottrani, P.R.: An analysis and characterisation of publicly available conceptual models. In: Johannesson, P., Lee, M.L., Liddle, S.W., Opdahl, A.L., López, Ó.P. (eds.) ER 2015. LNCS, vol. 9381, pp. 585–593. Springer, Heidelberg (2015)CrossRefGoogle Scholar
  14. 14.
    Keet, C.M., Fillottrani, P.R.: An ontology-driven unifying metamodel of UML class diagrams, EER and ORM2. Data Knowl. Eng. 98, 30–53 (2015)CrossRefGoogle Scholar
  15. 15.
    Khan, Z.C., Keet, C.M.: An empirically-based framework for ontology modularization. Appl. Ontol. 10(3–4), 171–195 (2015)CrossRefGoogle Scholar
  16. 16.
    Leather, S., Jeuring, J., Lh, A., Schuur, B.: Type-changing rewriting and semantics-preserving transformation. Sci. Comp. Prog. 112, 145–169 (2015)CrossRefGoogle Scholar
  17. 17.
    Mossakowski, T., Kutz, O., Codescu, M., Lange, C.: The distributed ontology, modeling and specification language. In: Proceedings of WoMo 2013. CEUR-WS, vol. 1081, Corunna, Spain, 15 September 2013Google Scholar
  18. 18.
    Motik, B., Patel-Schneider, P.F., Grau, B.C.: OWL 2 web ontology language: direct semantics. W3C recommendation, W3C, 27 October 2009.
  19. 19.
    Object Management Group: Meta Object Facility (MOF) 2.0 - Query/View/Transformation Specification.
  20. 20.
    Zhu, N., Grundy, J., Hosking, J.: Pounamu: a metatool for multi-view visual language environment construction. In: Proceedings of VLHCC 2004, Rome, 25–29 September 2004Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Zubeida C. Khan
    • 1
    • 2
  • C. Maria Keet
    • 1
    Email author
  • Pablo R. Fillottrani
    • 3
    • 4
  • Karina Cenci
    • 3
  1. 1.Department of Computer ScienceUniversity of Cape TownCape TownSouth Africa
  2. 2.Council for Scientific and Industrial ResearchPretoriaSouth Africa
  3. 3.Departamento de Ciencias e Ingeniería de la ComputaciónUniversidad Nacional del SurBahía BlancaArgentina
  4. 4.Comisión de Investigaciones CientíficasBuenos AiresArgentina

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