Skip to main content

Conceptual Model Interoperability: A Metamodel-driven Approach

  • Conference paper
Rules on the Web. From Theory to Applications (RuleML 2014)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 8620))

Abstract

Linking, integrating, or converting conceptual data models represented in different modelling languages is a common aspect in the design and maintenance of complex information systems. While such languages seem similar, they are known to be distinct and no unifying framework exists that respects all of their language features in either model transformations or inter-model assertions to relate them. We aim to address this issue using an approach where the rules are enhanced with a logic-based metamodel. We present the main approach and some essential metamodel-driven rules for the static, structural, components of ER, EER, UML v2.4.1, ORM, and ORM2. The transformations for model elements and patterns are used with the metamodel to verify correctness of inter-model assertions across models in different languages.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. See the list of collaborations (2014), http://www.tipharma.com/

  2. Atzeni, P., Cappellari, P., Torlone, R., Bernstein, P.A., Gianforme, G.: Model-independent schema translation. VLDB Journal 17(6), 1347–1370 (2008)

    Article  Google Scholar 

  3. Atzeni, P., Gianforme, G., Cappellari, P.: Data model descriptions and translation signatures in a multi-model framework. AMAI Mathematics and Artificial Intelligence 63, 1–29 (2012)

    Google Scholar 

  4. Banal-Estanol, A.: Information-sharing implications of horizontal mergers. International Journal of Industrial Organization 25(1), 31–49 (2007)

    Article  Google Scholar 

  5. Bollen, P.W.L.: A formal ORM-to-UML mapping algorithm research memo RM 02/016, Faculty of Economics and Business Administration. University of Maastricht (2002), http://arno.unimaas.nl/show.cgi?fid=46

  6. Bowers, S., Delcambre, L.M.L.: Using the uni-level description (ULD) to support data-model interoperability. Data & Knowledge Engineering 59(3), 511–533 (2006)

    Article  Google Scholar 

  7. Boyd, M., McBrien, P.: Comparing and transforming between data models via an intermediate hypergraph data model. J. on Data Semantics IV, 69–109 (2005)

    Google Scholar 

  8. Calvanese, D., Lenzerini, M., Nardi, D.: Unifying class-based representation formalisms. Journal of Artificial Intelligence Research 11, 199–240 (1999)

    MATH  MathSciNet  Google Scholar 

  9. Fill, H.G., Burzynski, P.: Integrating ontology models and conceptual models using a meta modeling approach. In: Proc. of 11th Int. Protégé Conference (2009); amsterdam 2009

    Google Scholar 

  10. Grundy, J., Venable, J.: Towards an integrated environment for method engineering. In: Proceedings of the IFIP TC8, WG8.1/8.2 Method Engineering, ME 1996, vol. 1, pp. 45–62 (1996)

    Google Scholar 

  11. Halevy, A.Y., Ashish, N., Bitton, D., Carey, M.J., Draper, D., Pollock, J., Rosenthal, A., Sikka, V.: Enterprise information integration: successes, challenges and controversies. In: Özcan, F. (ed.) SIGMOD Conference, pp. 778–787. ACM (2005)

    Google Scholar 

  12. Halpin, T.: Information Modeling and Relational Databases. Morgan Kaufmann Publishers, San Francisco (2001)

    Google Scholar 

  13. Hofstede, A.H.M.T., Proper, H.A.: How to formalize it? formalization principles for information systems development methods. Information and Software Technology 40(10), 519–540 (1998)

    Article  Google Scholar 

  14. Hovy, E.: Data and knowledge integration for e-government. In: Digital Government, pp. 219–231. Springer (2008)

    Google Scholar 

  15. Keet, C.M.: Ontology-driven formal conceptual data modeling for biological data analysis. In: Elloumi, M., Zomaya, A.Y. (eds.) Biological Knowledge Discovery Handbook: Preprocessing, Mining and Postprocessing of Biological Data, ch. 6, pp. 129–154. Wiley (2013)

    Google Scholar 

  16. Keet, C.M., Fillottrani, P.R.: Structural entities of an ontology-driven unifying metamodel for UML, EER, and ORM2. In: Cuzzocrea, A., Maabout, S. (eds.) MEDI 2013. LNCS, vol. 8216, pp. 188–199. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  17. Keet, C.M., Fillottrani, P.R.: Toward an ontology-driven unifying metamodel for UML class diagrams, EER, and ORM2. In: Ng, W., Storey, V.C., Trujillo, J.C. (eds.) ER 2013. LNCS, vol. 8217, pp. 313–326. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  18. Louie, B., Mork, P., Martin-Sanchez, F., Halevy, A., Tarczy-Hornoch, P.: Data integration and genomic medicine. J. of Biomedical Informatics 40(1), 5–16 (2007)

    Article  Google Scholar 

  19. Calo, K.M., Cenci, K.M., Fillottrani, P.R., Estevez, E.C.: Information sharing – benefits. Journal of Computer Science & Technology 12(2), 49–55 (2012)

    Google Scholar 

  20. Nelson, E.K., Piehler, B., Eckels, J., et al.: Labkey server: An open source platform for scientific data integration, analysis and collaboration. BMC Bioinformatics 12(1), 71 (2011)

    Article  Google Scholar 

  21. United Nations Department of Economic and Social Affairs: United Nations E-Government Survey 2010 – Leveraging e-government at a time of financial and economic crisis. Tech. Rep. ST/ESA/PAD/SER.E/131, United Nations (2010), http://unpan3.un.org/egovkb/global_reports/10report.htm

  22. Venable, J., Grundy, J.: Integrating and supporting Entity Relationship and Object Role Models. In: Papazoglou, M.P. (ed.) ER 1995 and OOER 1995. LNCS, vol. 1021, pp. 318–328. Springer, Heidelberg (1995)

    Chapter  Google Scholar 

  23. Zhu, N., Grundy, J., Hosking, J.: Pounamu: A metatool for multi-view visual language environment construction. IEEE Conf. on Visual Languages and Human-Centric Computing (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Fillottrani, P.R., Keet, C.M. (2014). Conceptual Model Interoperability: A Metamodel-driven Approach. In: Bikakis, A., Fodor, P., Roman, D. (eds) Rules on the Web. From Theory to Applications. RuleML 2014. Lecture Notes in Computer Science, vol 8620. Springer, Cham. https://doi.org/10.1007/978-3-319-09870-8_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-09870-8_4

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09869-2

  • Online ISBN: 978-3-319-09870-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics