Using Iconic Graphics in Entity-Relationship Diagrams

Masri, Kamal; Parker, Drew; Gemino, Andrew

doi:10.4018/jdm.2008070102

Cited by 34 publications

(25 citation statements)

References 49 publications

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“…This view is contradicted by research in diagrammatic reasoning, which shows that the form of representations has an equal, if not greater, influence on human understanding and problem solving performance as their content [42,76]. Empirical studies confirm that the visual appearance of RE notations significantly affects understanding, especially by novices [51,62].…”

Section: Previous Researchmentioning

confidence: 94%

“…Semantically transparent symbols reduce cognitive load because they have built-in mnemonics, making it easier to learn and remember what they mean [70]. Such representations improve speed and accuracy of understanding, especially by naïve users [7,51].…”

Section: Definition Of Principlementioning

confidence: 99%

“…For this reason, icons are routinely used in design of graphical user interfaces (GUIs) but surprisingly rarely in RE visual notations. Empirical studies show that replacing abstract shapes with concrete icons significantly improves understanding of RE models by novices [51]. Semantic transparency also applies to spatial relationships: certain spatial arrangements of visual elements predispose people towards a particular interpretation of how they are related even before the meaning of the elements is known [29,87].…”

Section: Definition Of Principlementioning

confidence: 99%

See 2 more Smart Citations

Visual syntax does matter: improving the cognitive effectiveness of the i* visual notation

2010

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Goal-oriented modelling is one of the most important research developments in the requirements engineering (RE) field. This paper conducts a systematic analysis of the visual syntax of i*, one of the leading goaloriented languages. Like most RE notations, i* is highly visual. Yet surprisingly, there has been little debate about or modification to its graphical conventions since it was proposed more than a decade ago. We evaluate the i* visual notation using a set of principles for designing cognitively effective visual notations (the Physics of Notations). The analysis reveals some serious flaws in the notation together with some practical recommendations for improvement. The results can be used to improve its effectiveness in practice, particularly for communicating with end users. A broader goal of the paper is to raise awareness about the importance of visual representation in RE research, which has historically received little attention.

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Section: Previous Researchmentioning

confidence: 94%

Section: Definition Of Principlementioning

confidence: 99%

Section: Definition Of Principlementioning

confidence: 99%

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Visual syntax does matter: improving the cognitive effectiveness of the i* visual notation

2010

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“…Semantically direct representations reduce cognitive load: their meaning can be perceived directly or easily. This kind of representations speeds-up concepts recognition, especially for novices [4,27]. According to [5], current visual notation design practice is characterised by:…”

Section: Background and Related Researchmentioning

confidence: 99%

On the Semantic Transparency of Visual Notations: Experiments with UML

Kouhen

Gherbi

Dumoulin

et al. 2015

SDL 2015: Model-Driven Engineering for Smart Cities

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Abstract. Graphical notations designed by committees in the context of standardization bodies, like Object Management Group (OMG), are widely used in the industry and academia. Naive users of these notations have limited background on visualization, documentation and specification of workflows, data or software systems. Several studies have pointed out the fact that these notations do not convey any particular semantics and their understanding is not perceptually immediate. As reported in these studies, this lack of semantic transparency increases the cognitive load to differentiate between concepts, slows down the learning and comprehension of the language constructs. This paper reports on a set of experiments that confirm the lack of semantic transparency of the Unified Modeling Language (UML) as designed by OMG and compares this standard to alternative solutions where naive users are involved in the design of the notations to speed-up the learning of these languages to new users.

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“…Some studies have shown that the use of additional or complementary graphical icons can assist users in processing representational information [39]. Mendling et al [40], for instance, argued that a suitable strategy for making process models more understandable is to develop iconic representations for the different activities in the process.…”

Section: Iconic Representationsmentioning

confidence: 99%

Exploring cognitive style and task-specific preferences for process representations

Figl

Recker

2014

Requirements Eng

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Process models describe someone's understanding of processes. Processes can be described using unstructured, semi-formal or diagrammatic representation forms. These representations are used in a variety of task settings, ranging from understanding processes to executing or improving processes, with the implicit assumption that the chosen representation form will be appropriate for all task settings. We explore the validity of this assumption by examining empirically the preference for different process representation forms depending on the task setting and cognitive style of the user. Based on data collected from 120 business school students, we show that preferences for process representation formats vary dependent on application purpose and cognitive styles of the participants. However, users consistently prefer diagrams over other representation formats. Our research informs a broader research agenda on task-specific applications of process modeling. We offer several recommendations for further research in this area.

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Using Iconic Graphics in Entity-Relationship Diagrams

Cited by 34 publications

References 49 publications

Visual syntax does matter: improving the cognitive effectiveness of the i* visual notation

Visual syntax does matter: improving the cognitive effectiveness of the i* visual notation

On the Semantic Transparency of Visual Notations: Experiments with UML

Exploring cognitive style and task-specific preferences for process representations

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