DOI QR코드

DOI QR Code

How Practitioners Perceive a Ternary Relationship in ER Conceptual Modeling

  • Jihae Suh (Seoul National University Big Data Institute) ;
  • Jinsoo Park (Management Information Systems at School of Business, Seoul National University) ;
  • Buomsoo Kim (Management Information Systems at School of Business, Seoul National University) ;
  • Hamirahanim Abdul Rahman (Management Information Systems at School of Business, Seoul National University)
  • Received : 2018.01.10
  • Accepted : 2018.04.13
  • Published : 2018.06.29

Abstract

Conceptual modeling is well suited as a subject that constitutes the "core" of the Information Systems (IS) discipline and has grown in response to IS development. Several modeling grammars and methods have been studied extensively in the IS discipline. Previous studies, however, present deficiencies in research methods and even put forward contradictory results about the ternary relationship in conceptual modeling. For instance, some studies contend that the semantics of a binary relationship are better for novices, but others argue that a ternary relationship is better than three binary relationships when the association among three entity types clearly exists. The objective of this research is to acquire complete and accurate understanding of the ternary relationship, specifically to understand practitioners' modeling performance when utilizing either a ternary or binary relationship. To the best of our knowledge, no previous work clearly compares real-world modeler performance differences between binary and ternary representations. By investigating practitioners' understanding of ternary relationship and identifying practitioners' cognition, this research can broaden the perspective on conceptual modeling.

Keywords

References

  1. Allen, G. N., and March, S. T. (2012). A research note on representing part-whole relations in conceptual modeling. MIS Quarterly, 36(3), 945-964.  https://doi.org/10.2307/41703488
  2. Batra, D., and Antony, S. R. (1994). Novice errors in conceptual database design. European Journal of Information Systems, 3(1), 57-69.  https://doi.org/10.1057/ejis.1994.7
  3. Batra, D., and Davis, J. G. (1992). Conceptual data modelling in database design: similarities and differences between expert and novice designers. International Journal of Man-Machine Studies, 37(1), 83-101.  https://doi.org/10.1016/0020-7373(92)90092-Y
  4. Batra, D., Hoffler, J., and Bostrom, R. P. (1990). Comparing representations with relational and EER models. Communications of the ACM, 33(2), 126-139.  https://doi.org/10.1145/75577.75579
  5. Bera, P., Burton-Jones, A., and Wand, Y. (2014). Research note-how semantics and pragmatics interact in understanding conceptual models. Information systems research, 25(2), 401-419.  https://doi.org/10.1287/isre.2014.0515
  6. Bloom, B. S., Engelhart, M. D., Hill, H., Furst, E., and Krathwhol, D. (1956). Taxonomy of Educational Objectives. The Classification of Educational Goals, Handbook I: Cognitive Domain. David McKay Company. Inc, New York. 
  7. Bodart, F., Patel, A., Sim, M., and Weber, R. (2001). Should optional properties be used in conceptual modelling? A theory and three empirical tests. Information systems research, 12(4), 384-405.  https://doi.org/10.1287/isre.12.4.384.9702
  8. Burton-Jones, A., Storey, V. C., Sugumaran, V., and Ahluwalia, P. (2005). A semiotic metrics suite for assessing the quality of ontologies. Data & Knowledge Engineering, 55(1), 84-102.  https://doi.org/10.1016/j.datak.2004.11.010
  9. Chen, P. P.-S. (1976). The entity-relationship model-toward a unified view of data. ACM Transactions on Database Systems (TODS), 1(1), 9-36.  https://doi.org/10.1145/320434.320440
  10. Chung, I., Nakamura, F., and Chen, P. P. (1981). A decomposition of relations using the entity-relationship approach. Proceedings of the Second International Conference on the Entity-Relationship Approach to Information Modeling and Analysis, North-Holland Publishing Co., Amsterdam 
  11. Compeau, D., Marcolin, B., Kelley, H., and Higgins, C. (2012). Research commentary-Generalizability of information systems research using student subjects-A reflection on our practices and recommendations for future research. Information systems research, 23(4), 1093-1109.  https://doi.org/10.1287/isre.1120.0423
  12. Cutrell, E., and Guan, Z. (2007). What are you looking for?: an eye-tracking study of information usage in web search. Proceedings of the SIGCHI conference on Human factors in computing systems, ACM. 
  13. Date, C. J. (2006). An introduction to database systems (8th ed.). Reading, MA, Addison-Wesley. 
  14. Davies, I., Green, P., Rosemann, M., Indulska, M., and Gallo, S. (2006). How do practitioners use conceptual modeling in practice? Data & Knowledge Engineering, 58(3), 358-380.  https://doi.org/10.1016/j.datak.2005.07.007
  15. Erickson, T. D., and Mattson, M. E. (1981). From words to meaning: A semantic illusion. Journal of Verbal Learning and Verbal Behavior, 20(5), 540-551.  https://doi.org/10.1016/S0022-5371(81)90165-1
  16. Ericsson, K. A., and Simon, H. A. (1984). Protocol analysis: Verbal reports as data. Cambridge, MA: MIT Press. 
  17. Ericsson, K. A., and Simon, H. A. (1993). Protocol analysis. MIT press Cambridge, MA. 
  18. Fidell, S., Silvati, L., Howe, R., Pearsons, K. S., Tabachnick, B., Knopf, R. C., Gramann, J., and Buchanan, T. (1996). Effects of aircraft overflights on wilderness recreationists. The Journal of the Acoustical Society of America, 100(5), 2909-2918.  https://doi.org/10.1121/1.417102
  19. Gemino, A., and Wand, Y. (2005). Complexity and clarity in conceptual modeling: comparison of mandatory and optional properties. Data & Knowledge Engineering, 55(3), 301-326.  https://doi.org/10.1016/j.datak.2004.12.009
  20. Hawryszkiewycz, I. T. (1991). Database analysis and design. Macmillan Press Ltd. Basingstoke, UK, UK. 
  21. Jones, T. H., and Song, I.-Y. (1996). Analysis of binary/ternary cardinality combinations in entity-relationship modeling. Data & Knowledge Engineering, 19(1), 39-64.  https://doi.org/10.1016/0169-023X(95)00036-R
  22. Jones, T. H., and Song, I.-Y. (2000). Binary equivalents of ternary relationships in entity-relationship modeling: a logical decomposition approach. Journal of Database Management, 11(2), 12. 
  23. Mayer, R. E. (1989). Models for understanding. Review of educational research, 59(1), 43-64.  https://doi.org/10.3102/00346543059001043
  24. McKee, R., and Rodgers, J. (1992). N-ary versus binary data modeling: A matter of perspective. Data Resource Management, 3(4), 22-32. 
  25. Newell, A., and Simon, H. A. (1972). Human problem solving. Prentice-Hall Englewood Cliffs, NJ. 
  26. Park, J. S. (2006). Real-time Data Integration, Semantic Interoperability, Ontology, Agent, Agent Communication Language, Asia Pacific Journal of Information Systems, 16(4), 151-178. 
  27. Park, J. S., and Choi, M. J. (2012). Data Warehousing Revisited: A Wal-Mart Case. Information Systems Review, 14(2), 47-63. 
  28. Park, J. S., and Chang, N. S. (2007). New Strategy of Potential-Based Customer Management: A Case of S-Card's ECI Approach. Information Systems Review, 9(2), 129-147. 
  29. Park, J. S., Sung, K. M., and Moon, S. W. (2010). IS Development and Operations, Ontology, METHONTOLOGY, OWL-DL, Ontology Development Methodology. Asia Pacific Journal of Information Systems, 20(2), 125-155. 
  30. Parsons, J., and Cole, L. (2005). What do the pictures mean? Guidelines for experimental evaluation of representation fidelity in diagrammatical conceptual modeling techniques. Data & Knowledge Engineering, 55(3), 327-342.  https://doi.org/10.1016/j.datak.2004.12.008
  31. Rosemann, M., Davies, I., and Green, P. (2003). The very model of modern BPM. Information Age, February/March, 24-29. 
  32. Sears, D. O. (1986). College sophomores in the laboratory: Influences of a narrow data base on social psychology's view of human nature. Journal of personality and social psychology, 51(3), 515. 
  33. Shanks, G., Moody, D., Nuredini, J., Tobin, D., and Weber, R. (2010). Representing classes of things and properties in general in conceptual modelling: An empirical evaluation. Journal of Database Management (JDM), 21(2), 1-25.  https://doi.org/10.4018/jdm.2010040101
  34. Shanks, G., Tansley, E., and Weber, R. (2003). Using ontology to validate conceptual models. Communications of the ACM, 46(10), 85-89.  https://doi.org/10.1145/944217.944244
  35. Siau, K., and Rossi, M. (2011). Evaluation techniques for systems analysis and design modelling methods -a review and comparative analysis. Information Systems Journal, 21(3), 249-268.  https://doi.org/10.1111/j.1365-2575.2007.00255.x
  36. Simsion, G., and Witt, G. (2004). Data modeling essentials. CA, San Francisco: Morgan Kaufmann Publishers. 
  37. Song, I.-Y., Jones, T. H., and Park, E. (1993). Binary relationship imposition rules on ternary relationships in ER modeling. Proceedings of the second international conference on Information and knowledge management, Washington, D.C., ACM. 
  38. Juhn, S. H. (1996). A Conceptual Model for It Impact Research. Asia Pacific Journal of Information Systems, 6(2), 201-220. 
  39. Teorey, T. J., Yang, D., and Fry, J. P. (1986). A logical design methodology for relational databases using the extended entity-relationship model. ACM Computing Surveys (CSUR), 18(2), 197-222.  https://doi.org/10.1145/7474.7475
  40. Tolman, E. C. (1959). Performance vectors: A theoretical and experimental attack upon emphasis, effect, and repression. American Psychologist, 14(1), 1. 
  41. Topi, H., and Ramesh, V. (2002). Human factors research on data modeling: a review of prior research, an extended framework and future research directions. Journal of Database Management (JDM), 13(2), 3-19.  https://doi.org/10.4018/jdm.2002040101
  42. Wand, Y., and Weber, R. (1993). On the ontological expressiveness of information systems analysis and design grammars. Information Systems Journal, 3(4), 217-237.  https://doi.org/10.1111/j.1365-2575.1993.tb00127.x
  43. Weber, R. (2003). Conceptual modelling and ontology: Possibilities and pitfalls. Journal of Database Management, 14(3), 1.