Software & Systems Modeling

, Volume 17, Issue 1, pp 269–294 | Cite as

An integrated multi-level modeling approach for industrial-scale data interoperability

  • Muzaffar Igamberdiev
  • Georg GrossmannEmail author
  • Matt Selway
  • Markus Stumptner
Theme Section Paper


Multi-level modeling is currently regaining attention in the database and software engineering community with different emerging proposals and implementations. One driver behind this trend is the need to reduce model complexity, a crucial aspect in a time of analytics in Big Data that deal with complex heterogeneous data structures. So far no standard exists for multi-level modeling. Therefore, different formalization approaches have been proposed to address multi-level modeling and verification in different frameworks and tools. In this article, we present an approach that integrates the formalization, implementation, querying, and verification of multi-level models. The approach has been evaluated in an open-source F-Logic implementation and applied in a large-scale data interoperability project in the oil and gas industry. The outcomes show that the framework is adaptable to industry standards, reduces the complexity of specifications, and supports the verification of standards from a software engineering point of view.


Multi-level modeling Interoperability Multi-level model reasoning F-Logic Multi-level model querying Multi-level model verification 



This research was supported by the South Australian Premier’s Research and Industry Fund.


  1. 1.
    Angele, J., Kifer, M., Lausen, G.: Ontologies in F-logic. In: Staab, S., Studer, R. (eds.) Handbook on Ontologies, pp. 45–70. Springer, Berlin (2009)Google Scholar
  2. 2.
    Asikainen, T., Männistö, T.: Nivel: a metamodelling language with a formal semantics. Softw. Syst. Model. 8(4), 521–549 (2009)CrossRefGoogle Scholar
  3. 3.
    Atkinson, C., Gerbig, R.: Melanie: multi-level modeling and ontology engineering environment. In: Proceedings of the 2nd International Master Class on Model-Driven Engineering: Modeling Wizards, p. 7. ACM (2012)Google Scholar
  4. 4.
    Atkinson, C., Gerbig, R.: Level-agnostic designation of model elements. In: Proceedings of ECMFA 2014, volume LNCS 8569, pp. 18–34. Springer (2014)Google Scholar
  5. 5.
    Atkinson, C., Gerbig, R., Fritzsche, M.: A multi-level approach to modeling language extension in the enterprise systems domain, information systems, vol. 54, pp. 289–307. Elsevier (2015). doi: 10.1016/
  6. 6.
    Atkinson, C., Gerbig, R., Tunjic, C.V.: Enhancing classic transformation languages to support multi-level modeling. Softw. Syst. Model. 14(2), 645–666 (2013)CrossRefGoogle Scholar
  7. 7.
    Atkinson, C., Grossmann, G., Kühne, T., de Lara, J. (eds). Proceedings of the Workshop on Multi-Level Modelling Co-Located with ACM/IEEE 17th International Conference on Model Driven Engineering Languages and Systems (MoDELS 2014), volume 1286 of CEUR Workshop Proceedings (2014)Google Scholar
  8. 8.
    Atkinson, C., Grossmann, G., Kühne, T., de Lara, J. (eds). Proceedings of the Workshop on Multi-Level Modelling Co-Located with ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems (MoDELS 2015) (2015)Google Scholar
  9. 9.
    Atkinson, C., Kennel, B., Goß, B.: The level-agnostic modeling language. In: Malloy, B., Staab, S., van den Brand, M. (eds.) Software Language Engineering, pp. 266–275. Springer, Berlin (2011)Google Scholar
  10. 10.
    Atkinson, C., Kennel, B., Goß, B.: Supporting constructive and exploratory modes of modeling in multi-level ontologies. In: Proceedings of 7th International Workshop on Semantic Web Enabled Software Engineering, Bonn (October 24, 2011) (2011)Google Scholar
  11. 11.
    Atkinson, C., Kühne, T.: Rearchitecting the UML infrastructure. ACM Trans. Model. Comput. Simul. 12(4), 290–321 (2002)CrossRefGoogle Scholar
  12. 12.
    Atkinson, C., Kühne, T.: Model-driven development: a metamodeling foundation. IEEE Softw. 20(5), 36–41 (2003)CrossRefGoogle Scholar
  13. 13.
    Atkinson, C., Kühne, T.: Reducing accidental complexity in domain models. Softw. Syst. Model. 7(3), 345–359 (2008)CrossRefGoogle Scholar
  14. 14.
    Balaban, M., Kifer, M.: Logic-based model-level software development with F-OML. In: Whittle, J., Clark, T., Kühne, T. (eds.) Model Driven Engineering Languages and Systems, pp. 517–532. Springer (2011)Google Scholar
  15. 15.
    Bock, J., Haase, P., Ji, Q., Volz, R.: Benchmarking OWL reasoners. In: Proceedings of the ARea2008 Workshop, Tenerife, Spain (June 2008)Google Scholar
  16. 16.
    Burgstaller, F., Steiner, D., Schrefl, M., Gringinger, E., Wilson, S., van der Stricht, S.: AIRM-based, fine-grained semantic filtering of notices to airmen. In: Integrated Communication, Navigation, and Surveillance Conference (ICNS), 2015, pp. D3–D1. IEEE (2015)Google Scholar
  17. 17.
    Cabot, J., Clarisó, R., Riera, D.: UMLtoCSP: A tool for the formal verification of UML/OCL models using constraint programming. In: Proceedings of the Twenty-Second IEEE/ACM International Conference on Automated Software Engineering, ASE ’07, pp. 547–548, New York, NY, USA, 2007. ACM (2007)Google Scholar
  18. 18.
    Cabot, J., Clarisó, R., Riera, D.: On the verification of UML/OCL class diagrams using constraint programming. J. Syst. Softw. 93, 1–23 (2014)CrossRefGoogle Scholar
  19. 19.
    Calvanese, D., De Giacomo, G., Lenzerini, M., Nardi, D., Rosati, R.: Information integration: conceptual modeling and reasoning support. In: Cooperative Information Systems, 1998, pp. 280–289. IEEE (1998)Google Scholar
  20. 20.
    Clark, T., Gonzalez-Perez, C., Henderson-Sellers, B.: A foundation for multi-level modelling. In: MULTI 2014–Multi-Level Modelling Workshop Proceedings, p. 43 (2014)Google Scholar
  21. 21.
    Daclin, Ni., Mallek-Daclin, S.: Towards a sustainable implementation of interoperability solutions: Bridging the gap between interoperability requirements and solutions. In: Enterprise Interoperability, volume 213 of Lecture Notes in Business Information Processing, pp. 73–82. Springer Berlin Heidelberg, (2015)Google Scholar
  22. 22.
    de Lara, J., Guerra, E., Cobos, R., Llorena, J.M.: Extending deep meta-modelling for practical model-driven engineering. Comput. J. 57(1), 36–58 (2014)CrossRefGoogle Scholar
  23. 23.
    De Lara, J., Guerra, E., Cuadrado, J.S.: When and how to use multilevel modelling. ACM TOSEM 24(2), 12 (2014)CrossRefGoogle Scholar
  24. 24.
    Demuth, A., Riedl-Ehrenleitner, M., Egyed, A.: Towards flexible, incremental, and paradigm-agnostic consistency checking in multi-level modeling environments. In: MULTI 2014–Multi-Level Modelling Workshop Proceedings, p. 73 (2014)Google Scholar
  25. 25.
    Egyed, A.: Automatically detecting and tracking inconsistencies in software design models. IEEE Trans. Softw. Eng. 37(2), 188–204 (2011)CrossRefGoogle Scholar
  26. 26.
    Fiatech. Advancing Interoperability for the Capital Projects Industry: A Vision Paper. Technical report, Fiatech (February 2012)Google Scholar
  27. 27.
    Gallaher, M.P., O’Connor, A.C. Jr. Dettbarn, J.L., Gilday, L.T: Cost Analysis of Inadequate Interoperability in the U.S. Capital Facilities Industry. Technical report, NIST (2004)Google Scholar
  28. 28.
    Giachetti, G., Valverde, F., Marín, B.: Interoperability for model-driven development: current state and future challenges. In: Sixth International Conference on Research Challenges in Information Science (RCIS), 2012, pp. 1–10. IEEE (2012)Google Scholar
  29. 29.
    Gonzalez-Perez, C., Henderson-Sellers, B.: A powertype-based metamodelling framework. Softw. Syst. Model. 5(1), 72–90 (2006)CrossRefGoogle Scholar
  30. 30.
    González, C.A., Cabot, J.: Formal verification of static software models in MDE: a systematic review. Inf. Softw. Technol. 56, 821–838 (2014)CrossRefGoogle Scholar
  31. 31.
    Guerra, E., de Lara, J.: Towards automating the analysis of integrity constraints in multi-level models. In: MULTI 2014—Multi-Level Modelling Workshop Proceedings, p. 63 (2014)Google Scholar
  32. 32.
    Haraty, R.A., Naous, M.F., Mourad, A.: Assuring consistency in mixed models. J. Comput. Sci. 5(4), 653–663 (2014)CrossRefGoogle Scholar
  33. 33.
    Horridge, M., Bechhofer, S.: The OWL API: a Java API for OWL ontologies. Semant. Web 2(1), 11–21 (2011)Google Scholar
  34. 34.
    Igamberdiev, M., Grossmann, G., Stumptner, M.: An implementation of multi-level modelling in F-logic. In: Proceedings of the Workshop on Multi-Level Modelling (MULTI14) Co-Located with MoDELS 2014, volume 1286 of CEUR, pp. 33–42 (2014)Google Scholar
  35. 35.
    ISO. ISO 15926: Industrial automation systems and integration–Integration of life-cycle data for process plants including oil and gas production facilities. Technical report, ISO (2004)Google Scholar
  36. 36.
    Jordan, A., Grossmann, G., Mayer, W., Selway, M., Stumptner, M.: On the application of software modelling principles on ISO 15926. In: Proceedings of the Modelling of the Physical World (MOTPW) Workshop at MODELS 2012. ACM (2012)Google Scholar
  37. 37.
    Kantner, D.: Specification and Implementation of a Deep OCL Dialect. Master’s thesis, Department of Business Informatics and Mathematics Chair of Software Engineering (2014)Google Scholar
  38. 38.
    Kennel, B.: A unified framework for multi-level modeling. PhD thesis, University of Mannheim (2012)Google Scholar
  39. 39.
    Kifer, M., Yang, G., Wan, H., Zhao, C., Kuznetsova, P., Liang, S.: Flora-2: user’s manual. Flora 2, 4 (2013)Google Scholar
  40. 40.
    Kim, S.-K., Carrington, D.: A formal mapping between uml models and object-z specifications. In: ZB 2000: Formal Specification and Development in Z and B, pp. 2–21. Springer (2000)Google Scholar
  41. 41.
    Kleiner, M., Albert, P., Bézivin, J.: Parsing sbvr-based controlled languages. In: Proceedings 12th International Conference on Model Driven Engineering Languages and Systems MODELS 2009, pp. 122–136, Denver, CO, October (2009)Google Scholar
  42. 42.
    Klokkhammer, O.: A diagrammatic approach to deep metamodelling. Master’s thesis, Department of Informatics University of Bergen (2014)Google Scholar
  43. 43.
    Lara, J., Guerra, E.: Deep meta-modelling with MetaDepth. In: TOOLS 2010, volume LNCS 6141, pp. 1–20. Springer (2010)Google Scholar
  44. 44.
    Lara, J., Guerra, E., Cuadrado, J.S.: Model-driven engineering with domain-specific meta-modelling languages. Springer SoSyM, Berlin (2013)Google Scholar
  45. 45.
    Lucas, F.J., Molina, F., Toval, A.: A systematic review of uml model consistency management. Inf. Softw. Technol. 51(12), 1631–1645 (2009)CrossRefGoogle Scholar
  46. 46.
    Mayer, W., Killisperger, P., Stumptner, M., Grossmann, G.: A declarative framework for work process configuration. Artif. Intell. Eng. Design Anal. Manuf. 25(2), 145–165 (2011)Google Scholar
  47. 47.
    Lucas, F.J., Molina, F., Toval, A.: A systematic review of uml model consistency management. Inf. Softw. Technol. 51(12), 1631–1645 (2009)CrossRefGoogle Scholar
  48. 48.
    Mayer, W., Stumptner, M., Grossmann, G., Jordan, A.: Semantic interoperability in the oil and gas industry: a challengingtestbed for semantic technologies. In: AAAI 2013 Fall Symposium on Semantics for Big Data (2013)Google Scholar
  49. 49.
    MIMOSA. Open Systems Architecture for Enterprise Application Integration (OSA-EAI) 3.2.3. Technical report, MIMOSA, (2012)Google Scholar
  50. 50.
    Segura A.M., Cuadrado, J.S., De Lara, J.: ODaaS: towards the model-driven engineering of open data applications as data services. In: Enterprise Distributed Object Computing Conference Workshops and Demonstrations (EDOCW), 2014 IEEE 18th International, pp. 335–339 (2014)Google Scholar
  51. 51.
    Neumayr, B., Jeusfeld, M.A., Schrefl, M., Schätz, C.: Dual deep instantiation and its ConceptBase implementation. In: Proceedings of CAiSE 2014, LNCS 8484, pp. 503–517. Springer (2014)Google Scholar
  52. 52.
    Neumayr, B., Schrefl, M., Thalheim, B.: Modeling techniques for multi-level abstraction. In: The Evolution of Conceptual Modeling, pp. 68–92. Springer (2011)Google Scholar
  53. 53.
    Rossini, A., de Lara, J., Guerra, E., Rutle, A., Wolter, U.: A formalisation of deep metamodelling. Formal Asp. Comput. 26(6), 1115–1152 (2014)MathSciNetCrossRefzbMATHGoogle Scholar
  54. 54.
    Schönböck, J., Kusel, A., Etzlstorfer, J., Kapsammer, E., Schwinger, W., Wimmer, M., Wischenbart, M.: CARE—a constraint-based approach for re-establishing conformance relationships. In APCCM 2014, CRPIT vol. 154, pp. 19–28. ACS (2014)Google Scholar
  55. 55.
    Selway, M., Mayer, W., Stumptner, M.: Semantic interpretation of requirements through cognitive grammar and configuration. In: Proceedings of Pacific Rim Conference on Artificial Intelligence (PRICAI) 2014, volume LNCS 8862, pp. 496–510. Springer (2014)Google Scholar
  56. 56.
    Soeken, M., Wille, R., Kuhlmann, M., Gogolla, M., Drechsler, R.: Verifying uml/ocl models using boolean satisfiability. In: Proceedings of the Conference on Design, Automation and Test in Europe, DATE ’10, pp. 1341–1344, 3001 Leuven, Belgium, Belgium, 2010. European Design and Automation Association (2010)Google Scholar
  57. 57.
    Stumptner, M., Friedrich, G., Haselböck, A.: Generative constraint-based configuration of large technical systems. Artif. Intell. Eng. Design Anal. Manuf. 12(4), 307–320 (1998)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Muzaffar Igamberdiev
    • 1
  • Georg Grossmann
    • 1
    Email author
  • Matt Selway
    • 1
  • Markus Stumptner
    • 1
  1. 1.Advanced Computing Research Centre, School of IT and Mathematical SciencesUniversity of South AustraliaMawson LakesAustralia

Personalised recommendations