Evaluation of the Ontological Completeness and Clarity of Object-Oriented Conceptual Modelling Grammars

Evaluation of the Ontological Completeness and Clarity of Object-Oriented Conceptual Modelling Grammars

Prabodha Tilakaratna, Jayantha Rajapakse
Copyright: © 2017 |Pages: 26
DOI: 10.4018/JDM.2017040101
(Individual Articles)
No Current Special Offers


Several research studies have concluded that modelling grammars that support the Object-Oriented (OO) methodology focus more on modelling system design and implementation phenomena than real-world phenomena in IS users' domains. Thus, the purpose of this research study was to evaluate the suitability of OO modelling grammars for conceptual modelling. Although the research work focused on one widely used OO modelling grammar—namely, the Unified Modelling Language (UML)—the approach developed can be applied to any OO modelling grammar. The first phase of this research study focused on evaluating all UML constructs and identifying a subset of UML constructs that are capable of representing real-world phenomena in user domains. The second phase was an empirical evaluation of the identified subset of UML constructs. The results of this empirical evaluation suggest that instead of using all UML constructs the subset of UML constructs is better suited for conceptual modelling.
Article Preview


Modelling is the essence of the Information System (IS) development process. It can be divided into two main genres: conceptual modelling and system modelling. Conceptual modelling represents phenomena that occur in a selected real-world scenario by transforming human perceptions of that real-world scenario into a model of perceived reality (Weber, 2003; Whitten, Bentley, and Dittman, 2001). A conceptual model is later used as the basis for building a system model during the design phase of IS development.

Conceptual modelling is important because IS development often commences with conceptual modelling. Hence, errors in a conceptual model are likely to propagate to subsequent phases of the IS development process (Wand and Weber, 2002). Such errors become more costly to fix if they are discovered in later IS development phases.

Conceptual and system modelling primarily emphasize the data and process characteristics of a real-world scenario and the IS being developed. In the early history of both conceptual and system modelling, the data and process characteristics were captured and modelled separately (Milton, Rajapakse, and Weber, 2010). The IS community found that real-world phenomena and the IS domain cannot be represented precisely when this distinction is made. As such, in the 1980s, a new methodology for IS development was introduced—the Object-Oriented (OO) methodology (Eliens, 2000).

Nevertheless, researchers have found that OO modelling grammars do not have all the constructs needed to completely and clearly1 represent the types of phenomena that occur in the real world (Evermann and Wand, 2005a, 2005b, 2009; Opdahl and Henderson-Sellers, 2002a; Opdahl, Henderson-Sellers, and Barbier, 2000, 2001). The reason is that the fundamental notion of object in the OO methodology was introduced for the development of system models rather than conceptual models (Tilakaratna and Rajapakse, 2012). In contrast, the primary objective of conceptual modelling is the representation of real-world scenarios. In this regard, use of OO modelling grammars for conceptual modelling is problematic. Accordingly, our research study is motivated by the desire to evaluate the completeness and clarity of OO modelling grammars for conceptual modelling.

Evermann (2003, 2005) and Evermann and Wand (2001, 2005a, 2009) have already evaluated an OO modelling grammar, the Unified Modelling Language (UML), in terms of its suitability for conceptual modelling purposes. They chose UML because it is evolving into the most prominent and widely accepted OO modelling grammar (Evermann and Wand, 2005a). UML has 14 diagrammatic notations that are capable of modelling different views (e.g., static structure, interactions, internal and external phenomena) of an IS. Nevertheless, Evermann (2003, 2005) and Evermann and Wand (2001, 2005a, 2009) evaluated only a few of the constructs that exist in three UML diagrammatic notations—namely, class diagrams, state-machine diagrams, and activity diagram.

Therefore, in this research study, we extend Evermann and Wand’s research work in three ways. First, we analyse all constructs in the 14 UML diagrammatic notations to identify the subset that are suitable for conceptual modelling purposes. Second, using an ontological approach, we evaluate whether this subset can represent any type of real-world phenomena completely and clearly. Third, we assess empirically whether practicing system analysts find the subset to be useful for conceptual modelling purposes.

Complete Article List

Search this Journal:
Volume 34: 3 Issues (2023)
Volume 33: 5 Issues (2022): 4 Released, 1 Forthcoming
Volume 32: 4 Issues (2021)
Volume 31: 4 Issues (2020)
Volume 30: 4 Issues (2019)
Volume 29: 4 Issues (2018)
Volume 28: 4 Issues (2017)
Volume 27: 4 Issues (2016)
Volume 26: 4 Issues (2015)
Volume 25: 4 Issues (2014)
Volume 24: 4 Issues (2013)
Volume 23: 4 Issues (2012)
Volume 22: 4 Issues (2011)
Volume 21: 4 Issues (2010)
Volume 20: 4 Issues (2009)
Volume 19: 4 Issues (2008)
Volume 18: 4 Issues (2007)
Volume 17: 4 Issues (2006)
Volume 16: 4 Issues (2005)
Volume 15: 4 Issues (2004)
Volume 14: 4 Issues (2003)
Volume 13: 4 Issues (2002)
Volume 12: 4 Issues (2001)
Volume 11: 4 Issues (2000)
Volume 10: 4 Issues (1999)
Volume 9: 4 Issues (1998)
Volume 8: 4 Issues (1997)
Volume 7: 4 Issues (1996)
Volume 6: 4 Issues (1995)
Volume 5: 4 Issues (1994)
Volume 4: 4 Issues (1993)
Volume 3: 4 Issues (1992)
Volume 2: 4 Issues (1991)
Volume 1: 2 Issues (1990)
View Complete Journal Contents Listing