A semiotic analysis of unified modeling language graphical notations | Requirements Engineering Skip to main content
Springer Nature Link
Log in

A semiotic analysis of unified modeling language graphical notations

  • Original Article
  • Published:
Requirements Engineering Aims and scope Submit manuscript

Abstract

Unified modeling language (UML) is the standard modeling language for object-oriented system development. Despite its status as a standard, UML has a fuzzy formal specification and a weak theoretical foundation. Semiotics, the study of signs, provides a good theoretical foundation for UML research because graphical notations (or visual signs) of UML are subjected to the principles of signs. In our research, we use semiotics to study the effectiveness of graphical notations in UML. We hypothesized that the use of iconic signs as UML graphical notations leads to representation that is more accurately interpreted and that arouses fewer connotations than the use of symbolic signs. An open-ended survey was used to test these hypotheses. The results support our propositions that iconic UML graphical notations are more accurately interpreted by subjects and that the number of connotations is lower for iconic UML graphical notations than for symbolic UML graphical notations. The results have both theoretical and practical significance. This study illustrates the usefulness of using semiotics as a theoretical underpinning in analyzing, evaluating, and comparing graphical notations for modeling constructs. The results of this research also suggest ways and means of enhancing the graphical notations of UML modeling constructs.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Alemán J, Álvarez A (2001) Seamless formalizing the UML semantics through metamodeling. In: Siau K et al (eds) Unified modeling language: systems analysis, design and development issues. Idea Group Publishing, Hershey

    Google Scholar 

  2. Andersen P (1990) A theory of computer semiotics. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  3. Barjis J, Chong S, Dietz J, Liu K (2002) Development of agent-based e-commerce systems using semiotic approach and DEMO transaction concept. Int J Inf Technol Decis Mak 1(3):491–510

    Article  Google Scholar 

  4. Barron T, Chiang R, Storey V (1999) A semiotics framework for information system classification and development. Decis Support Syst 25:1–17. doi:10.1016/S0167-9236(98)00088-8

    Article  Google Scholar 

  5. Barthes R, Smith M, Knott R, Berger J, Alty J (1994) Minimizing conceptual baggage: making choices about metaphor. In: People and Computers IX. HCI’94. Glasgow, August, pp 179–194

  6. Batra D (2007) Cognitive complexity in data modeling: causes and recommendations. Requir Eng 12(4):231–244. doi:10.1007/s00766-006-0040-y

    Article  MathSciNet  Google Scholar 

  7. Booch G, Rumbaugh J, Jacobson I (2005) The unified modeling language user guide, 2nd edn. Addison Wesley, New York

    Google Scholar 

  8. Chandler D (2002) Semiotics for beginners. Available online at http://www.aber.ac.uk/media/Documents/S4B/semiotic.html

  9. Condon C, Perry M, O’Keefe R (2004) Denotation and connotation in the human-computer interface: the ‘save as…’ command. Behav Inf Technol 23(1):21–31. doi:10.1080/01449290310001637415

    Article  Google Scholar 

  10. De Souza C (1993) The semiotic engineering of user interface languages. Int J Man Mach Stud 39(7):53–773

    Google Scholar 

  11. Desouza K, Hensgen T (2002) On information in organizations: an emergent information theory and semiotic framework. Emergence 4(3):95–114. doi:10.1207/S15327000EM0403-07

    Article  Google Scholar 

  12. Dobbing B, Parsons J (2008) Dimensions of UML diagram use: a survey of practitioners. J Database Manage 19(1):1–18

    Google Scholar 

  13. Dykman N, Griss M, Kessler R (1999) Nine suggestions for improving UML extensibility. In: UML’99—the unified modeling language. 1723:236–248

  14. Erickson J, Siau K (2007) Theoretical and practical complexity of modeling methods. Commun ACM 50(8):46–51. doi:10.1145/1278201.1278205

    Article  Google Scholar 

  15. Evermann J, Wand Y (2009) Ontology based object-oriented domain modeling: representing behavior. J Database Manage 20(1):48–77

    Google Scholar 

  16. Fiske J (1982) Introduction to communications studies. Routledge, London

    Google Scholar 

  17. Fontoura M, de Lucena C (2001) Extending UML to improve the representation of design patterns. J Object Oriented Program 13(11):12–19

    Google Scholar 

  18. Galloway A (1997) Questionnaire design and analysis. Available online at http://www.tardis.ed.ac.uk/~kate/qmcweb/qcont.htm

  19. Gemino A, Parker D (2009) Use case diagrams in support of use case modeling: deriving understanding from the picture. J Database Manage 20(1):1–24

    Google Scholar 

  20. Hensgen T, Desouza K, Evaristoc J, Kraft G (2003) Playing the “cyber terrorism game” towards a semiotic definition. Hum Syst Manage 22:51–61

    Google Scholar 

  21. Liu K (2004) Virtual, distributed and flexible organizations: Studies in organizational semiotics. Kluwer, Dordrecht

    Google Scholar 

  22. Liu K (2005) Requirement reengineering from legacy information systems using semiotics techniques. Syst Signs Actions Int J Commun Inf Technol Work 1(1):38–61

    Google Scholar 

  23. Liu K, Clarke R, Andersen P, Stamper R (2001) Information, organization and technology: studies in organizational semiotics. Kluwer, Dordrecht

    Google Scholar 

  24. Liu K, Clarke R, Andersen P, Stamper R (2002) Organizational semiotics: evolving a science of information systems. Kluwer, Dordrecht

    Google Scholar 

  25. Loucopoulos P, Kadir WMNW (2008) BROOD: business rules-driven object oriented design. J Database Manage 19(1):41–73

    Google Scholar 

  26. Mehler A, Clarke R (2002) Systemic functional hypertexts. An architecture for social semiotic hypertext systems. In: New directions in humanities computing. Proceedings of the 14th joint international conference of the association for literary and linguistic computing and the association for computers and the humanities (ALLC/ACH ’02), July 24–28. University of Tübingen, Seiten, pp 68–69

  27. Meziane F, Athanasakis N, Ananiadou S (2008) Generating natural language specifications from UML class diagrams. Requir Eng 13(1):1–18. doi:10.1007/s00766-007-0054-0

    Article  Google Scholar 

  28. Morris C (1946) Signs. Language and behavior. Prentice-Hall, New York

    Google Scholar 

  29. Nadin M (1981) The integrating function of the sign in Peirce’s semiotic. In: Ketner KL, Ransdell JM, Eisele C, Fisch M, Hardwick C (eds) Proceedings of the C.S. Peirce Bicentennial International Congress, vol 23. pp 363–366

  30. Nadin M (1997) Signs and system, in signs and systems. A semiotic introduction to systems design. Cambridge University Press, Cambridge

    Google Scholar 

  31. OMG (2003) OMG unified modeling language specification. Object Management Group, Version 1.5

  32. Osgood C, George J, Percy H (1957) The measurement of meaning. University of Illinois Press, Urbana

    Google Scholar 

  33. Peirce C (1931) Collected writings (8 vols). In: Hartshorne C et al (eds) Harvard University Press, Cambridge, p 58

  34. Reinhartz-Berger I, Sturm A (2008) Enhancing UML models: a domain analysis approach. J Database Manage 19(1):74–94

    Google Scholar 

  35. Rossi M, Brinkkemper S (1996) Complexity metrics for systems development methods and techniques. Inf Syst 21(2):209–227

    Article  Google Scholar 

  36. Shen Z, Siau K (2003) An empirical evaluation of UML notational elements using a concept mapping approach. In: Paper presented at the 2003 International Conference of Information System (ICIS 2003)

  37. Siau K (1999) Information modeling and method engineering: a psychological perspective. J Database Manage 10(4):44–50

    Google Scholar 

  38. Siau K (2004) Informational and computational equivalence in comparing information modeling methods. J Database Manage 15(1):73–86

    Google Scholar 

  39. Siau K (2007) The future of information systems engineering. Requir Eng 12(4):199–202. doi:10.1007/s00766-007-0059-8

    Article  Google Scholar 

  40. Siau K, Cao Q (2001) Unified modeling language—a complexity analysis. J Database Manage 12(1):26–34

    Google Scholar 

  41. Siau K, Erickson J, Lee L (2005) Theoretical versus practical complexity: the case of UML. J Database Manage 16(3):40–57

    Google Scholar 

  42. Siau K, Lee L (2004) Are use case and class diagrams complementary in requirements analysis?—an experimental study on use case and class diagrams in UML. Requir Eng 9(4):229–237. doi:10.1007/s00766-004-0203-7

    Article  Google Scholar 

  43. Siau K, Loo P (2006) Identifying difficulties in learning UML. Inf Syst Manage 23(3):43–51

    Article  Google Scholar 

  44. Siau K, Rossi M (2009) Systems analysis and design: evaluation techniques for conceptual and data modeling methods. Inf Syst J

  45. Siau K, Tan X (2005) Improving the quality of conceptual modeling using cognitive mapping techniques. Data Knowl Eng 55(3):343–365. doi:10.1016/j.datak.2004.12.006

    Article  Google Scholar 

  46. Siau K, Tan X (2006) Using cognitive mapping techniques to supplement UML and UP in information requirements determination. J Comput Inf Syst 46(5):59–66

    Google Scholar 

  47. Siau K, Tan X (2008) Use of cognitive mapping techniques in information systems development. J Comput Inf Syst 48:49–57

    Google Scholar 

  48. Siau K, Tian Y (2001) The complexity of unified modeling language—a GOMS analysis. Paper presented at the 2001 International Conference of Information System (ICIS 2001)

  49. Siau K, Tian Y (2002) Analyzing unified modeling language using GOMS. Paper presented at the 12th Workshop on Information Technology and Systems. Barcelona, Spain

  50. Siau K, Wang Y (2007) Cognitive evaluation of information modeling methods. Inf Softw Technol 49(5):455–474. doi:10.1016/j.infsof.2006.07.001

    Article  Google Scholar 

  51. Simons H, Graham I (1999) 30 Things that go wrong in object modelling with UML 1.3. In: Kilov H et al (eds) Precise behavioral specification of businesses and systems. Kluwer, Dordrecht

    Google Scholar 

  52. Smolander K, Rossi M (2008) Conflicts, compromises, and political decisions: methodological challenges of enterprise-wide E-business architecture creation. J Database Manage 19(1):19–40

    Google Scholar 

  53. Song X, Osterweil L (1992) Toward objective, systematic design-method comparisons. IEEE Softw 9(3):43–53. doi:10.1109/52.136166

    Article  Google Scholar 

  54. Stamper R (1996) Signs, norms, and information systems. In: Holmqvist B et al (eds) Signs at work. Walter De Gruyter, Berlin

    Google Scholar 

  55. Stamper R, Liu K, Hafkamp M, Ades Y (2000) Understanding the roles of signs and norms in organizations—a semiotic approach to information system design. Behav Inf Technol 19(1):15–27. doi:10.1080/014492900118768

    Article  Google Scholar 

  56. Underwood M (2003) Introductory models and basic concepts: semiotics. Available on line at http://www.cultsock.ndirect.co.uk/MUHome/cshtml/semiomean/semio1.html

  57. VanderMeer D, Dutta K (2009) Applying learner-centered design principles to UML sequence diagrams. J Database Manage 20(1):25–47

    Google Scholar 

  58. Wand Y, Weber R (1993) On the ontological expressiveness of information systems analysis and design grammars. J Inf Syst 3(4):217–237

    Article  Google Scholar 

  59. Zhang H, Kishore R, Ramesh R (2007) Semantics of the MibML conceptual modeling grammar: an ontological analysis using the Bunge-Wang-Weber framework. J Database Manage 18(1):1–19

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Management, 209 College of Business Administration, University of Nebraska-Lincoln, Lincoln, NE, 68588-0491, USA

    Keng Siau & Yuhong Tian

Authors
  1. Keng Siau
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuhong Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Keng Siau.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Siau, K., Tian, Y. A semiotic analysis of unified modeling language graphical notations. Requirements Eng 14, 15–26 (2009). https://doi.org/10.1007/s00766-008-0071-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00766-008-0071-7

Keywords

Search

Navigation