Advertisement

Formalisation of ORM Derivation Rules and Their Mapping into OWL

  • Francesco SportelliEmail author
  • Enrico Franconi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10033)

Abstract

Object-Role Modelling (ORM) is a framework for modelling and querying information at the conceptual level. It comes to support the design of large-scale industrial applications allowing the users to model easily the domain. Derivation rules are additional ORM constructs which capture some relevant information of the domain that cannot be expressed in the standard ORM2 language. In this paper, we identify the first-order fragment of subtype derivation rules (without arithmetic operators and aggregation functions) and we provide a provably correct mapping into OWL. This enables complete automated reasoning with ORM2 conceptual schemas enriched by derivation rules, such as detecting inconsistencies and redundancies and deriving implicit constructs. We illustrate the implementation of our formalisation in ORMiE, a plugin for the NORMA ORM2 extension of Microsoft Visual Studio, which automatically maps ORM2 conceptual schemas with derivation rules into OWL and uses a description logic prover as a background reasoning engine.

Keywords

Description Logic Conceptual Schema Entity Type Inference Engine Class Expression 
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.

References

  1. 1.
    Artale, A., Franconi, E.: Extending DLR with labelled tuples, projections, functional dependencies and objectification. In: Proceedings of the 29th International Workshop on Description Logics (2016). http://ceur-ws.org/Vol-1577/paper_6.pdf
  2. 2.
    Curland, M., Halpin, T.: The NORMA software tool for ORM 2. In: Soffer, P., Proper, E. (eds.) CAiSE Forum 2010. LNBIP, vol. 72, pp. 190–204. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-17722-4_14 CrossRefGoogle Scholar
  3. 3.
    Fillottrani, P.R., Franconi, E., Tessaris, S.: The ICOM 3.0 intelligent conceptual modelling tool and methodology. Semant. Web 3(3), 293–306 (2012). http://dx.doi.org/10.3233/SW-2011-0038 Google Scholar
  4. 4.
    Fillottrani, P.R., Keet, C.M., Toman, D.: Polynomial encoding of ORM conceptual models in CFDI. In: Proceedings of the 28th International Workshop on Description Logics (2015). http://ceur-ws.org/Vol-1350/paper-50.pdf
  5. 5.
    Franconi, E., Mosca, A., Solomakhin, D.: ORM2 encoding into description logics. In: 2012 International Description Logics workshop (DL-2012) (2012)Google Scholar
  6. 6.
    Franconi, E., Mosca, A.: Towards a core ORM2 language (research note). In: Demey, Y.T., Panetto, H. (eds.) OTM 2013. LNCS, vol. 8186, pp. 448–456. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-41033-8_58 CrossRefGoogle Scholar
  7. 7.
    Franconi, E., Mosca, A., Oriol, X., Rull, G., Teniente, E.: Logic foundations of the OCL modelling language. In: Fermé, E., Leite, J. (eds.) JELIA 2014. LNCS (LNAI), vol. 8761, pp. 657–664. Springer, Heidelberg (2014). doi: 10.1007/978-3-319-11558-0_49 Google Scholar
  8. 8.
    Franconi, E., Mosca, A., Solomakhin, D.: The formalization of ORM2 and its encoding in OWL2. In: International Workshop on Fact-Oriented Modeling (ORM 2012) (2012)Google Scholar
  9. 9.
    Gottlob, G., Leone, N.: The complexity of acyclic conjunctive queries. J. ACM 48(3), 431–498 (2001). http://doi.acm.org/10.1145/382780.382783 MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Halpin, T.: A logical analysis of information systems: static aspects of the data-oriented perspective. Ph.D. thesis (July 1989)Google Scholar
  11. 11.
    Halpin, T.: Adding derivation rules and join paths in NORMA. Tech. rep, ORM Solutions, August 2013Google Scholar
  12. 12.
    Halpin, T.: Object-Role Modeling Fundamentals: A Practical Guide to Data Modeling with ORM, 1st edn. Technics Publications, Basking Ridge (2015)Google Scholar
  13. 13.
    Halpin, T.A.: Object-role modeling: principles and benefits. IJISMD 1(1), 33–57 (2010). http://dx.doi.org/10.4018/jismd.2010092302 Google Scholar
  14. 14.
    Halpin, T.A., Morgan, T.: Information Modeling and Relational Databases, 2nd edn. Morgan Kaufmann, Burlington (2008)Google Scholar
  15. 15.
    Horridge, M., Drummond, N., Goodwin, J., Rector, A.L., Stevens, R., Wang, H.: The manchester OWL syntax. In: Proceedings of the OWLED 2006 Workshop on OWL: Experiences and Directions (2006). http://ceur-ws.org/Vol-216/submission_9.pdf
  16. 16.
    Jarrar, M.: Towards automated reasoning on ORM schemes. In: Parent, C., Schewe, K.-D., Storey, V.C., Thalheim, B. (eds.) ER 2007. LNCS, vol. 4801, pp. 181–197. Springer, Heidelberg (2007). doi: 10.1007/978-3-540-75563-0_14 CrossRefGoogle Scholar
  17. 17.
    Jarrar, M., Meersman, R.: Ontology engineering – the DOGMA approach. In: Dillon, T.S., Chang, E., Meersman, R., Sycara, K. (eds.) Advances in Web Semantics I. LNCS, vol. 4891, pp. 7–34. Springer, Heidelberg (2008). doi: 10.1007/978-3-540-89784-2_2. http://Portal.acm.org/Citation.cfm?Id=1505684 CrossRefGoogle Scholar
  18. 18.
    NORMA: Natural Object-Role Modeling (ORM) Architect for Visual Studio, product on Sourceforge (2016). https://sourceforge.net/projects/orm/
  19. 19.
    Queralt, A., Artale, A., Calvanese, D.: OCL-lite: finite reasoning on UML/OCL conceptual schemas. Data Knowl. Eng. 73, 1–22 (2012). http://dx.doi.org/10.1016/j.datak.2011.09.004 CrossRefGoogle Scholar
  20. 20.
    Yannakakis, M.: Algorithms for acyclic database schemes. In: 7th International Conference on Very Large Data Bases (VLDB), pp. 82–94 (1981)Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.KRDB Research CentreFree University of Bozen-BolzanoBolzanoItaly

Personalised recommendations