Metamodel-Based Information Integration at Industrial Scale

  • Stefan Berger
  • Georg Grossmann
  • Markus Stumptner
  • Michael Schrefl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6395)


Flexible data integration has been an important IT research goal for decades. About ten years ago, a significant step was taken with the introduction of declarative methods (e.g., Clio). Since this work, mostly based on classic dependency analysis, extensions have been developed that express more powerful semantic relationships. However, much of this work has remained focused at the relational database (i.e., relatively low) level, and many of the extensions revert to specific algorithms and function specifications. At the same time, models have evolved to incorporate more powerful semantics (object or ontology-based methods). The work presented in the paper uses flexible metamodel-based mapping definitions that enable a model-driven engineering approach to integration, allowing declarative mapping specifications to be automatically executed at runtime within a single-formalism and single-tool framework. The paper reports how to create executable mappings for large-scale data integration scenarios with an interactive graphical tool.


General-purpose modeling languages model-based development tools and meta-tools 


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  1. 1.
    ISO 15926 – Industrial automation systems and integration: Integration of life-cycle data for process plants including oil and gas production facilities: Part 2: Data model. ISO (2003)Google Scholar
  2. 2.
    ISO 10303 – Industrial automation systems and integration: Product data representation and exchange: Part 11: Description methods: EXPRESS language reference manual. ISO (2004)Google Scholar
  3. 3.
    ISO 13374 – Condition monitoring and diagnostics of machines: Data processing, communication and presentation: Part 2: Data processing. ISO, Geneva (2007)Google Scholar
  4. 4.
    ISO 15926 – Industrial automation systems and integration: Integration of life-cycle data for process plants including oil and gas production facilities: Part 7: Implementation methods for the integration of distributed system – Template methodology. ISO, Geneva (2008)Google Scholar
  5. 5.
    Open Systems Architecture for Enterprise Application Integration – Version 3.2.2 Specification, MIMOSA (2010),
  6. 6.
    Agt, H., Bauhoff, G., Cartsburg, M., Kumpe, D., Kutsche, R.-D., Milanovic, N.: Metamodeling foundation for software and data integration. In: Proc. 3rd Intl. United Information Systems Conf. (UNISCON), pp. 328–339. Springer, Heidelberg (2009)Google Scholar
  7. 7.
    Batres, R., West, M., Leal, D., Price, D., Masaki, K., Shimada, Y., Fuchino, T., Naka, Y.: An upper ontology based on ISO 15926. Comp. & Chemical Eng. 31(5-6), 519–534 (2007)CrossRefGoogle Scholar
  8. 8.
    Bengtsson, M.: Standardization issues in condition based maintenance. In: Proc. 16th Intl. Cong. on Condition Monitoring and Diagnostic Eng. Mgmt., pp. 651–660. Univ. Press (2003)Google Scholar
  9. 9.
    Draheim, D., Himsl, M., Jabornig, D., Küng, J., Leithner, W., Regner, P., Wiesinger, T.: Concept and pragmatics of an intuitive visualization-oriented metamodeling tool. J. Vis. Lang. Comput. 21(3), 157–170 (2010)CrossRefGoogle Scholar
  10. 10.
    Grossmann, G., Ren, Y., Schrefl, M., Stumptner, M.: Behavior based integration of composite business processes. In: van der Aalst, W.M.P., Benatallah, B., Casati, F., Curbera, F. (eds.) BPM 2005. LNCS, vol. 3649, pp. 186–204. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  11. 11.
    Haas, L.M., Hentschel, M., Kossmann, D., Miller, R.J.: Schema and data: A holistic approach to mapping, resolution and fusion in information integration. In: Proc. 28th Intl. Conf. on Conceptual Modeling (ER), pp. 27–40. Springer, Heidelberg (2009)Google Scholar
  12. 12.
    Hakkarainen, S., Hella, L., Strasunskas, D., Tuxen, S.: A semantic transformation approach for ISO 15926. In: Roddick, J., Benjamins, V.R., Si-said Cherfi, S., Chiang, R., Claramunt, C., Elmasri, R.A., Grandi, F., Han, H., Hepp, M., Lytras, M.D., Mišić, V.B., Poels, G., Song, I.-Y., Trujillo, J., Vangenot, C. (eds.) ER Workshops 2006. LNCS, vol. 4231, pp. 281–290. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Lin, S., Gao, J., Koronios, A., Chanana, V.: Developing a data quality framework for asset management in engineering organisations. IJIQ 1(1), 100–126 (2007)CrossRefGoogle Scholar
  14. 14.
  15. 15.
    Pelekis, N., Theodoulidis, B., Kopanakis, I., Theodoridis, Y.: Literature review of spatio-temporal database models. The Knowledge Eng. Review 19(3), 235–274 (2004)CrossRefGoogle Scholar
  16. 16.
    Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. VLDB J. 10(4), 334–350 (2001)CrossRefMATHGoogle Scholar
  17. 17.
    Template specifications for ISO15926 part 7,
  18. 18.
    Shtelma, M., Cartsburg, M., Milanovic, N.: Executable domain specific language for message-based system integration. In: Schürr, A., Selic, B. (eds.) MODELS 2009. LNCS, vol. 5795, pp. 622–626. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  19. 19.
    Smith, B.: Against idiosyncrasy in ontology development. In: Frontiers in Artificial Intelligence and Applications (FOIS), vol. 150, pp. 15–26. IOS Press, Amsterdam (2006)Google Scholar
  20. 20.
    Thiagarajan, R.K., Mayer, W., Stumptner, M.: A generative framework for service process composition. In: Baresi, L., Chi, C.-H., Suzuki, J. (eds.) ICSOC-ServiceWave 2009. LNCS, vol. 5900, pp. 358–363. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  21. 21.
    Tryfona, N., Price, R., Jensen, C.S.: Conceptual models for spatio-temporal applications. In: Sellis, T.K., Koubarakis, M., Frank, A., Grumbach, S., Güting, R.H., Jensen, C., Lorentzos, N.A., Manolopoulos, Y., Nardelli, E., Pernici, B., Theodoulidis, B., Tryfona, N., Schek, H.-J., Scholl, M.O. (eds.) Spatio-Temporal Databases. LNCS, vol. 2520, pp. 79–116. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  22. 22.
    Yuan, M.: Use of a three-domain repesentation to enhance GIS support for complex spatiotemporal queries. Trans. on GIS 3(2), 137–159 (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Stefan Berger
    • 1
  • Georg Grossmann
    • 1
  • Markus Stumptner
    • 1
  • Michael Schrefl
    • 1
  1. 1.Advanced Computing Research CentreUniversity of South AustraliaAdelaideAustralia

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