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Understanding Constraint Expressions in Large Conceptual Schemas by Automatic Filtering

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 7532)

Abstract

Human understanding of constraint expressions (also called schema rules) in large conceptual schemas is very difficult. This is due to the fact that the elements (entity types, attributes, relationship types) involved in an expression are defined in different places in the schema, which may be very distant from each other and embedded in an intricate web of irrelevant elements. The problem is insignificant when the conceptual schema is small, but very significant when it is large. In this paper we describe a novel method that, given a set of constraint expressions and a large conceptual schema, automatically filters the conceptual schema, obtaining a smaller one that contains the elements of interest for the understanding of the expressions. We also show the application of the method to the important case of understanding the specification of event types, whose constraint expressions consists of a set of pre and postconditions. We have evaluated the method by means of its application to a set of large conceptual schemas. The results show that the method is effective and efficient. We deal with conceptual schemas in UML/OCL, but the method can be adapted to other languages.

Keywords

  • Constraints
  • Large Conceptual Schemas
  • Filtering

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References

  1. Lenat, D.B.: Cyc: a large-scale investment in knowledge infrastructure. Commun. ACM 38(11), 33–38 (1995)

    CrossRef  Google Scholar 

  2. Object Management Group (OMG): Unified Modeling Language (UML) Superstructure Specification, version 2.3 (May 2010)

    Google Scholar 

  3. Beeler, G.: HL7 Version 3–An object-oriented methodology for collaborative standards development. International Journal of Medical Informatics 48(1-3), 151–161 (1998)

    CrossRef  Google Scholar 

  4. Object Management Group (OMG): Object Constraint Language Specification (OCL), version 2.0 (February 2010)

    Google Scholar 

  5. Hevner, A., March, S., Park, J., Ram, S.: Design science in information systems research. Mis Quarterly 28(1), 75–105 (2004)

    Google Scholar 

  6. Bauerdick, H., Gogolla, M., Gutsche, F.: Detecting OCL Traps in the UML 2.0 Superstructure: An Experience Report. In: Baar, T., Strohmeier, A., Moreira, A., Mellor, S.J. (eds.) UML 2004. LNCS, vol. 3273, pp. 188–196. Springer, Heidelberg (2004)

    Google Scholar 

  7. Ramirez, A.: Esquema conceptual de Magento, un sistema de comerç electrónic. Technical report. Universitat Politécnica de Catalunya (2011), http://hdl.handle.net/2099.1/12294

  8. Tort, A., Olivé, A.: The osCommerce conceptual schema. Technical report, Universitat Politécnica de Catalunya (2007), http://hdl.handle.net/2099.1/5301

  9. Frias, L., Queralt, A., Olivé, A.: EU-Rent car rentals specification. Technical report, Universitat Politécnica de Catalunya (2003), http://www.lsi.upc.edu/~techreps/files/R03-59.zip

  10. Villegas, A., Olivé, A.: A Method for Filtering Large Conceptual Schemas. In: Parsons, J., Saeki, M., Shoval, P., Woo, C., Wand, Y. (eds.) ER 2010. LNCS, vol. 6412, pp. 247–260. Springer, Heidelberg (2010)

    CrossRef  Google Scholar 

  11. Tzitzikas, Y., Hainaut, J.-L.: How to Tame a Very Large ER Diagram (Using Link Analysis and Force-Directed Drawing Algorithms). In: Delcambre, L.M.L., Kop, C., Mayr, H.C., Mylopoulos, J., Pastor, Ó. (eds.) ER 2005. LNCS, vol. 3716, pp. 144–159. Springer, Heidelberg (2005)

    CrossRef  Google Scholar 

  12. Auddino, A., Dennebouy, Y., Dupont, Y., Fontana, E., Spaccapietra, S., Tari, Z.: SUPER – Visual interaction with an object-based ER model. In: Pernul, G., Tjoa, A.M. (eds.) ER 1992. LNCS, vol. 645, pp. 340–356. Springer, Heidelberg (1992)

    CrossRef  Google Scholar 

  13. Lanzenberger, M., Sampson, J., Rester, M.: Visualization in ontology tools. In: Intl. Conf. on Complex, Intelligent and Software Intensive Systems, pp. 705–711. IEEE Computer Society (2009)

    Google Scholar 

  14. Shoval, P., Danoch, R., Balabam, M.: Hierarchical entity-relationship diagrams: the model, method of creation and experimental evaluation. Requirements Engineering 9(4), 217–228 (2004)

    CrossRef  Google Scholar 

  15. Moody, D.L., Flitman, A.: A Methodology for Clustering Entity Relationship Models - A Human Information Processing Approach. In: Akoka, J., Bouzeghoub, M., Comyn-Wattiau, I., Métais, E. (eds.) ER 1999. LNCS, vol. 1728, pp. 114–130. Springer, Heidelberg (1999)

    CrossRef  Google Scholar 

  16. Campbell, L.J., Halpin, T.A., Proper, H.A.: Conceptual schemas with abstractions making flat conceptual schemas more comprehensible. Data & Knowledge Engineering 20(1), 39–85 (1996)

    CrossRef  MATH  Google Scholar 

  17. Kuflik, T., Boger, Z., Shoval, P.: Filtering search results using an optimal set of terms identified by an artificial neural network. Information Processing & Management 42(2), 469–483 (2006)

    CrossRef  MATH  Google Scholar 

  18. Hanani, U., Shapira, B., Shoval, P.: Information filtering: Overview of issues, research and systems. User Modeling and User-Adapted Interaction 11(3), 203–259 (2001)

    CrossRef  MATH  Google Scholar 

  19. Belkin, N.J., Croft, W.B.: Information filtering and information retrieval: two sides of the same coin? Commun. ACM 35, 29–38 (1992)

    CrossRef  Google Scholar 

  20. Villegas, A., Sancho, M.-R., Olivé, A.: A Tool for Filtering Large Conceptual Schemas. In: De Troyer, O., Bauzer Medeiros, C., Billen, R., Hallot, P., Simitsis, A., Van Mingroot, H. (eds.) ER Workshops 2011. LNCS, vol. 6999, pp. 353–356. Springer, Heidelberg (2011)

    CrossRef  Google Scholar 

  21. Olivé, À.: Definition of Events and Their Effects in Object-Oriented Conceptual Modeling Languages. In: Atzeni, P., Chu, W., Lu, H., Zhou, S., Ling, T.-W. (eds.) ER 2004. LNCS, vol. 3288, pp. 136–149. Springer, Heidelberg (2004)

    CrossRef  Google Scholar 

  22. Downs, E., Clare, P., Coe, I.: Structured Systems Analysis and Design Method: Application and Context, 2nd edn. Prentice-Hall (1992)

    Google Scholar 

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Villegas, A., Olivé, A., Sancho, MR. (2012). Understanding Constraint Expressions in Large Conceptual Schemas by Automatic Filtering. In: Atzeni, P., Cheung, D., Ram, S. (eds) Conceptual Modeling. ER 2012. Lecture Notes in Computer Science, vol 7532. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34002-4_4

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  • DOI: https://doi.org/10.1007/978-3-642-34002-4_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34001-7

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