What Makes a Good Diagram? Improving the Cognitive Effectiveness of Diagrams in IS Development

Daniel Moody Department of Information Systems and Change Management

University of Twente, Enschede, Netherlands E-mail: d.l.moody@bbt.utwente.nl

Abstract. Diagrams play a critical role in IS development. Despite this, ISD practitioners receive little or no instruction on how to produce “good” diagrams. In the absence of this, they are forced to rely on their intuition and experience, and make layout decisions that distort information or convey unintended meanings. The design of ISD graphical notations is ad hoc and unscientific: choice of conventions is based on personal taste rather than sci-entific evidence. Also, existing notations use a very limited graphic vocabulary and thus fail to exploit the potential communication power of diagrams. This paper describes a set of principles for producing “good” diagrams, which are defined as diagrams that communicate effectively. These provide practical guidance for both designers and users of ISD diagram-ming notations and are soundly based on theoretical and empirical evidence from a wide range of disciplines. We conclude that radical change is required to ISD diagramming prac-tices to achieve effective user-developer communication.

Diagrams form a critical part of the “language” of IS development: most ISD techniques rely heavily on graphical representations. For example, UML 2.0 con-sists of 13 types of models, all of which are represented in graphical form [29]. The primary reason for using diagrams in IS development is to facilitate commu-nication. In particular, diagrams are believed to be more effective than text for communicating with end users. Effective user-developer communication is critical for successful development of information systems.

1.1 Cognitive Effectiveness: What is a “Good” Diagram? A diagram is a sentence in a graphical language [24]. The primary purpose of any language is to communicate. Therefore a “good” diagram is one which communi-cates effectively. Communication (or cognitive) effectiveness is measured by the speed, ease and accuracy with which the information content can be understood. The cognitive effectiveness of diagrams is one of the most widely held assump-tions in the ISD field. However cognitive effectiveness is not an intrinsic property of diagrams but something that must be designed into them [19].

1.2 Current State of Practice Despite the importance of diagrams in IS development, practitioners typically receive little or no instruction in how to produce effective diagrams. As a result, they are forced to rely on their intuition and experience (which is often wrong), and make layout decisions that distorts information or conveys unintended

1. IINTRODUCTION

judgements about “aesthetics” (what looks good), which they are not qualified to make as they typically lack expertise in graphic design. Also, what looks good is not always what communicates most effectively. Current ISD diagramming prac-tices are based on erroneous assumptions about what makes diagrams effective and flawed heuristics about how best to construct them. Examples of commonly-used heuristics include avoiding line crossings, using zigzag lines and expanding symbols to fit labels. While these are designed to improve readability of diagrams, in most cases they have the opposite effect. Despite this, such practices have been perpetuated over time and have become so entrenched that they are often docu-mented as “best practices” [e.g. 1].

The design of ISD diagramming notations is also largely ad hoc and unscien-tific. Decisions about how to graphically represent constructs are based on personal taste, intuition or consensus rather than on scientific evidence. There is usually no theoretical or empirical justification for conventions used, perhaps re-flecting a belief that it does not really matter which conventions are chosen. ISD diagramming notations also use a perceptually limited repertoire of graphical tech-niques and thus fail to exploit the potential power of diagrams [33]. The same graphical symbols (variants of boxes and arrows) are used over and over again while some of the most effective graphical techniques such as colour, spatial lay-out, size and value are not used at all or used informally [33]. Finally, most ISD diagramming notations are inconsistent with principles of graphic design. This is not surprising as designers of ISD notations typically lack training or expertise in graphic design. However while it is common in other areas of ISD practice (e.g. user interface design, web development) to get advice from graphic design spe-cialists, notation designers rarely do the same.

1.3 Current State of Research The perceptual characteristics (visual appearance or form) of diagrams have been grossly understated by ISD researchers. While issues of semantics or content (what constructs to include in a notation) are treated as matters of substance, de-tails of graphical syntax (how to visually represent these constructs) are treated as being of little or no consequence. Choice of graphical conventions is seen by re-searchers (like notation designers) as a matter of aesthetics or personal taste rather than effectiveness [14]. Research in diagrammatical reasoning suggests the exact opposite: the cognitive effectiveness of diagrams is primarily determined by their perceptual characteristics [19, 33]. Even slight changes in graphical representation can have dramatic impacts on understanding and problem solving performance. The extent to which diagrams exploit perceptual features largely explains why some diagrams are effective and others are not [19]. This suggests that the form of diagrams is just as important – if not more – than their content.

1.4 Objectives of this Paper Most ISD diagrams do not communicate effectively and actually act as a barrier rather than an aid to user-developer communication [17, 28, 39]. Field studies

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messages. Decisions about presentation of diagrams tend to be driven by subjective

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show that end users understand ISD diagrams very poorly and that most develop-ers don’t even show diagrams to their users [13, 14, 28, 37]. The fault for this lies with educators, notation designers and researchers, who have largely ignored is-sues of graphical representation or treated them in an ad hoc way. The aim of this paper is to provide a scientific basis for the use of diagrams in IS development. We argue that ISD diagramming practice should be evidence based: decisions about what graphical conventions to use (language level) and layout of individual diagrams (sentence level) should be based on evidence about cognitive effective-ness rather than subjective notions of aesthetics. The major focus of this research is on improving the effectiveness of communication with non-specialists (end users) as this is most critical for improving for improving the quality of the IS development process.

In order to produce more cognitively effective diagrams, we need to consider two things [49]:

The language of graphics: the techniques available for encoding information graphically. Clearly, the better our command of the language, the more ef-fectively we will be able to communicate.

Human graphical information processing: how diagrams are processed by the human mind. This is necessary to evaluate the cognitive effectiveness of alternative representations.

2.1 The Language of Graphics The seminal work in the field of graphical communication is Jacques Bertin’s “Semiology of Graphics” [5]. This is considered by many to be for graphic design what the periodic table is for chemistry. Bertin identified eight elementary visual variables which can be used to graphically encode information (Figure 1). These are categorised into planar variables (the two spatial dimensions) and retinal vari-ables (features of the retinal image).

Figure 1. Visual Variables [5]

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2. TTHEORIES OF GRAPHICAL COMMUNICATION

set of atomic building blocks that can be used to construct any graphical represen-tation – similar to the way the elements of the periodic table can be used to construct any chemical compound. Different visual variables are suitable for en-coding different types of information. For example, colour can be used to encode nominal data but not ordinal or ratio data because it is not psychologically ordered [18]. The choice of visual variables has a major impact on cognitive effectiveness as it affects both speed and accuracy of interpretation [9, 22, 50].

2.2 Human Graphical Information Processing Figure 2 shows a model of human graphical information processing, which re-flects current research in human cognition and visual perception. This consists of four major processing stages:

Perceptual discrimination: features of the retinal image (i.e. visual variables)

integration) [21, 41]. Based on this initial processing, the diagram is parsed into discrete elements based on common visual properties and separated from the background (figure-ground segregation) [30, 50].

Perceptual configuration: diagram elements are grouped together (possibly recursively) based on their visual characteristics [30, 50]. The Gestalt Laws of Perception define a set of rules for how visual stimuli are organised into perceptual groups [46].

Cognitive ProcessingPerceptual Processing

Perceptual discrimination

Perceptual configuration

Working memory

Long term memory

attention

Diagram

retinal image

Figure 2. Model of Graphical Information Processing

Working memory (WM): all or part of the processed image is brought into WM for active processing and interpretation under conscious control of at-tention. Perceptual precedence determines the order in which elements are attended to [51]. WM is a temporary storage area which synchronises rapid perceptual processes with slower cognitive processes. It has very limited ca-pacity and duration and is a known bottleneck in graphical information processing [18, 22].

Long term memory (LTM): information extracted from the diagram is inte-grated with prior knowledge stored in LTM. LTM is a permanent storage area which has unlimited capacity and duration but is relatively slow. There are two types of prior knowledge relevant to diagram understanding: domain knowledge (knowledge about the represented domain) and notational knowl-edge (knowledge about the diagramming notation). In the case of notation experts (i.e. IS developers), notational knowledge is likely to be encoded in a diagram schema, which largely automates the process of diagram interpreta-

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are detected, some serially, some in parallel, across the visual field (feature

The set of visual variables define a “vocabulary” for graphical communication: a

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tion [34]. Domain experts (i.e. end users) are unlikely to have such a schema as they interact with such diagrams infrequently and therefore interpretation will be much more error-prone and will require significant conscious effort.

Perceptual processes are automatic, pre-attentive, very fast and mostly executed in parallel while cognitive processes operate under conscious control of attention and are relatively slow, effortful and sequential. A major basis for the cognitive advan-tages of diagrams is that they shift some of the processing burden to the perceptual system, freeing up cognitive resources for other tasks [36].

In this section, we define a set of evidence-based principles for producing cogni-tively effective ISD diagrams. These are based on theoretical and empirical evidence from a wide range of disciplines including cartography, conceptual mod-elling, cognitive psychology, communication theory, computer graphics, diagrammatic reasoning, education, graphic design, graph drawing, human-computer interaction, information visualisation, linguistics, multimedia design, psychophysics, semiotics, statistics, technical writing, typography, visual percep-tion and visual programming.

3.1

Perceptual discrimination is the first step in graphical information processing (Figure 2). Accurate discrimination of diagram elements is a necessary prerequi-site for further processing. There are two aspects to discriminability [18]:

Absolute discriminability: the ability to see diagram elements and separate them from the background.

Relative discriminability: the ability to differentiate between different types of diagram elements.

Absolute discriminability is determined by three primary factors: Size: diagram elements (and also textual labels) need to be a certain mini-

mum size to be seen and recognised correctly [48]. The optimal size of elements for human perception have been empirically established for both visual elements and text [2, 40].

Contrast: according to the Gestalt Figure-Ground principle, the greater the contrast between diagram elements and the background, the more readily ob-jects will be detected and recognised [30, 46]. Contrast can be achieved by using clearly different surface properties (colour, texture or value) between diagram elements and the background. Adequate contrast should also be es-tablished between textual labels and their background.

Proximity: discernibility of diagram elements decreases with proximity of other elements [52]. This relates to the use of white space, which is one of

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Discriminability: Diagram Elements should be Easy to See and Differentiate from one another

the major design elements in graphic design [47]. There is no empirical basis for choosing the optimal spacing between elements but for most types of ISD diagrams 1–1.5 shape widths provides adequate separation.

Relative discriminability is determined by the number and size of differences be-tween symbols used to represent different constructs. The greater the perceptual variation between symbols used to represent different constructs, the faster and more accurately they will be recognised [51]. If differences are too subtle, errors in interpretation and ambiguity can result. In particular, requirements for dis-criminability are much higher for novices (end users) than for experts [7, 8].

3.2 Manageable Complexity: Diagrams should not

One of the most common mistakes in ISD diagramming practice is to show too much information on a single diagram. This results in “absurdly complex dia-grams” that are a barrier rather than an aid to communication [17]. The reason for this is that the amount of information that can be effectively conveyed by a single diagram is limited by human perceptual and cognitive abilities:

Perceptual limits: The ability to visually discriminate between diagram ele-ments decreases with their number and proximity [23]. In general, the difficulty of discerning diagram elements increases quadratically with dia-gram size [31]. The root cause of discriminability problems with ISD diagrams (Principle 1) is excessive complexity.

Cognitive limits: The number of diagram elements that can be comprehended at a time is limited by working memory capacity, which is believed to be “seven plus or minus two” concepts at a time [3, 21, 45]. When this is ex-ceeded, a state of cognitive overload ensues and comprehension degrades rapidly [20, 26].

One of the most effective ways of reducing the complexity of large systems is to divide them into smaller subsystems or modules. This is called decomposition or modularisation [4]. In the context of diagrams, this means that large diagrams should be divided into perceptually and cognitively manageable “chunks” (seven plus or minus two elements per diagram). Experimental studies show that modu-larising ISD diagrams in this way improves end user understanding and verification accuracy by more than 50% [27].

3.3

In most ISD diagrams, all elements look the same: there is no way of telling which are most important [17]. Such representations act as very poor information filters. Also, because there is no clear entry point or processing sequence, it makes them hard to access for novices and leads to inefficient and haphazard processing [6, 33]. The visual variables (Figure 2) can be used to create a clear perceptual prece-dence or visual hierarchy among diagram elements. The most effective visual variables for emphasis are those suitable for encoding ordinal data as emphasis

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Exceed Perceptual and Cognitive Limits

Emphasis: The Relative Importance of Diagram Elements should be Clearly Shown

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defines a partial ordering over diagram elements. The most important concepts should be emphasised (highlighted) to bring them to the readers’ attention, while less important or background elements should be de-emphasised (lowlighted) [52]. This defines a clear processing sequence which facilitates more efficient processing [6, 51]. Research in diagrammatic reasoning shows that directing at-tention to the most important concepts can dramatically improve understanding and problem-solving performance [6, 11, 52].

3.4

One of the unique problems with ISD diagrams compared to diagrams used in most other disciplines is that systems are typically represented using multiple dia-grams. For example, UML consists of 13 different types of diagrams, each of which represents the system from a different perspective. The need to manage complexity (Principle #2) further exacerbates the problem by creating multiple diagrams of each type. This results in a complex network of diagrams that can be difficult to understand as a whole and navigate through. Using multiple diagrams places additional cognitive demands on the user to mentally integrate information from different diagrams and to keep track of where they are in the network of dia-grams [38, 42]. For such representations to be cognitively effective, the diagramming notation must provide explicit mechanisms to support [16]:

Conceptual integration: enabling the reader to integrate information from separate diagrams into a coherent mental representation of the problem.

Perceptual integration: providing perceptual cues (orienting, contextual and directional information) to aid navigation between diagrams.

There are a range of mechanisms which can be used to achieve cognitive integra-tion, such as summary diagrams [16], signposting [25] and spatial contiguity [44].

3.5

Perceptually direct representations are representations whose interpretation is spontaneous or natural, in that their meaning can be extracted automatically by the perceptual system. Such representations are highly efficient as they offload inter-pretation effort from the cognitive system to the perceptual system: extracting meaning from the diagram becomes effort-free.

Representation of constructs: Icons are symbols which perceptually resemble the objects they represent [32]. Using icons to represent constructs reduces cognitive load because they have built-in mnemonics: the association with the referent concept can be perceived directly, and does not have to be learnt [33]. Icons also make diagrams more visually appealing, speed up recogni-tion and recall, and improve intelligibility to naïve users [7, 8].

Representation of relationships: Perceptual directness also applies to repre-sentation of relationships among diagram elements. Certain spatial

What Makes a Good Diagram?

Cognitive Integration: When Multiple Diagrams are used, Explicit Mechanisms should be Included to Support Cognitive Integration

Perceptual Directness: Make use of Perceptually Direct Representations

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configurations of diagram elements predispose people towards a particular interpretation even before the meaning of the elements is understood. For example, left to right arrangement of objects suggests causality or sequence while placing objects inside other objects suggests class membership [12, 48]. Diagramming notations can be designed to exploit these intuitively un-derstood spatial arrangements to increase ease and accuracy of interpretation.

3.6

In most ISD diagrams, there is no clear structure or grouping among diagram ele-ments. This leads to inefficient encoding in WM, as each diagram element must be encoded as a separate “chunk” [18]. The Gestalt Laws of Perception define a set of empirically validated principles for how the human perceptual system organises visual stimuli into perceptual units [46]. These can be used to group related dia-gram elements together and so facilitate perceptual configuration (Figure 3). In this way, This facilitates more efficient use of WM, as each group of elements can be encoded as a chunk rather than encoding each element separately [26]. This reduces cognitive load and frees up cognitive resources for other information processing tasks [10, 22]. Perceptual grouping provides both an alternative and a complement to decomposition (Principle 2). Organising diagram elements into groups expands the number of elements that can be shown on each diagram with-out exceeding cognitive limits [10]. This reduces the total number of diagrams required, which in turn reduces the need for cognitive integration (Principle 4).

3.7Identification is an important concept in cartography [35] but is given little ex-plicit attention in ISD diagramming practice. There are two aspects to identification [5]:

External identification: this defines the correspondence between the diagram and the represented world. Each diagram should have a title, which should be clearly recognisable as such by its size and placement [18]. This should summarise the content of the diagram (the part of the referent domain it rep-resents). Diagram elements (both nodes and links) should also be clearly labelled, using terminology familiar to domain experts to help trigger domain knowledge in LTM. Labels should be clearly grouped with their referent ob-jects using Gestalt principles [15].

Internal identification: this defines the correspondence between graphical conventions and their meaning. The diagram type should be clearly identi-fied to trigger the appropriate diagram schema in LTM (if one exists) and reduce likelihood of misinterpretation. In addition, a legend or key should be included, summarising the graphical conventions used. This should be in-cluded within the frame of each diagram rather than on a separate sheet of paper or document to avoid problems of cognitive integration [25, 43, 44].

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Structure: Organise Diagram Elements into Perceptual Groups

Identification: Diagrams should be Clearly Labelled

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3.8

Most ISD diagramming notations use a very limited graphical vocabulary and use only one of the eight available visual variables to encode information: shape. Shape is one of the least cognitively efficient variables as it can only be used to encode nominal data and is detected serially [23]. Visual expressiveness refers to the number of different visual variables used to encode information. Using multi-ple visual variables results in a perceptually enriched representation which uses multiple, parallel channels of communication. It also helps increase visual interest and attention. Using multiple visual variables to convey the same information (redundant coding) improves accuracy of communication and counteracts noise.

3.9

Graphic complexity is defined as the number of different graphical conventions used in a notation [28]. Experimental studies show that human ability to discrimi-nate between perceptually distinct alternatives (the span of absolute judgement) is around six categories [26]. Most ISD diagramming notations currently in use ex-ceed this significantly: for example, UML Class Diagrams have a graphic complexity of 14. One solution to this problem is increase the number of percep-tual dimensions (i.e. visual variables) on which constructs differ. This has been shown empirically to increase human ability to discriminate between stimuli [26]. Another solution is not to show everything in graphical form: diagrams are useful for showing some types of information (e.g. structure, relationships) but not oth-ers (e.g. detailed business rules): some information can be more effectively represented in textual form [33].

This paper has described a set of principles for producing “good” diagrams, which are defined as diagrams that are cognitively effective (i.e. that communicate effec-tively). These principles are soundly based on theoretical and empirical evidence from a range of disciplines rather than on intuition, experience and convention like most principles used in ISD practice. The principles can be either applied at the level of diagramming notations (language level) or individual diagrams (sen-tence level). Some principles apply mainly at the language level, others apply mainly at the diagram level but most apply at both to at least some extent. In ap-plying these principles to current ISD diagramming practices, the conclusion is that radical change is required to achieve effective user-developer communication.

4.1 Theoretical Significance The theoretical contributions of this paper are as follows:

(a) It highlights the importance of the visual aspects (form) of ISD notations, which have been grossly understated in ISD research and practice.

What Makes a Good Diagram?

Visual Expressiveness: Use the Fu ll Range of Visual Variables

Graphic Simplicity: The Numbe r o f Different Graphical Conventions should be Limited

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4. CCONCLUSION

(b) It defines a descriptive model of how diagrams communicate, based on re-search in graphic design, cognition and visual perception. This provides a theoretical basis for evaluating the visual aspects of ISD notations which complements methods used to evaluate semantic aspects.

(c) It defines a set of prescriptive principles for producing cognitively effec-tive diagrams. These define causal relationships between the perceptual characteristics of diagrams and efficiency and effectiveness of human in-formation processing. These help to increase our understanding of what makes ISD diagrams effective or ineffective and also represent theoretical propositions which can be empirically tested.

4.2 Practical Significance The principles defined in this paper provide practical guidance for both designers and users of ISD diagramming notations. Importantly, they are not abstract, theo-retical principles but highly specific and operational principles, which could be easily incorporated into current ISD practices. They can be used by ISD practitio-ners to produce diagrams that communicate more effectively with their customers. They can also be used by ISD notation designers to develop diagramming nota-tions that more effectively exploit human perceptual and cognitive capabilities.

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