The effect of graphic style on data model interpretation

Abstract

Abstract. Graphic data models are commonly used as a tool for presentation of information structures in the design, implementation, use and maintenance of the databases that support information systems. The methods proposed for database design assume that the use of graphic data models will enhance understanding of system specifications by both the end‐users and the implementers of the system. For this assumption to hold, the information presented in the graphic data model must be readily comprehensible so that the design, represented by the model, can be confirmed and implemented correctly. The lack of standard representations for graphic models has led to a variety of graphic styles. To date, there has been little focus on studying the effect graphic style has on model comprehension. We have studied the effect of three graphic styles proposed for data models on model legibility and interpretation. Our study shows a significant variation in model interpretation that can be attributed to the graphic syntax used. Graphic style appears to influence which model elements are included in the interpretation, as well as the way data models are read.

On the Cognitive Effectiveness of Routing Symbols in Process Modeling Languages

“…Low perceptual discriminability can lead to misunderstandings. Research showed that for instance rectangles and diamonds in ER diagrams are easily confused (see [20]). On the other hand, if different symbols in a notation have similar attributes as color or shape, they are likely to be recognized as belonging together.…”

“…Using swimlanes in activity diagrams, for example, includes both planar variables for depicting information on who is working on an activity (see [18]). -Graphic Parsimony: Parsimony is an indicator of graphical model complexity and is determined by the use of embedded symbols and distinct graphic symbols [20]. High graphic complexity of a modeling language, e.g., the use of too many constructs and routing elements in one model, may impair understanding and therefore should be avoided [15].…”

Evaluation of Selected Control Programming Languages for Process Engineers by Means of Cognitive Effectiveness and Dimensions

“…We selected AD, SC and SFC, though, due to their prevalence in the domain [17] [32] and their ease of use, especially for process engineers, who are often programming novices. There exist different descriptive methods for the comparison of dissimilar languages of these sub-requirements.…”

“…The AD and SC symbols are international standard [32]. The common graphical design of SFC is also defined in a norm [17]. These defined symbols of AD, SC, and SFC are widely used and internationally understood.…”

“…Hence, its understandability is higher than that of a conventional nonhierarchical one [10]. It was shown that understandability and maintainability in graphical programming languages are better than in textual programming languages [11]- [17]. Therefore, we do not consider textual programming languages in this paper.…”