OMG tutorial Physics of Notations - Object Management … 1 OMG Technical Conference: Full Day Tutorial The Physics† of Notations: Designing Diagramming Notations That Work Presenter:

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OMG Technical Conference: Full Day Tutorial

The Physics† of Notations: Designing Diagramming Notations That Work

Presenter: Dr Daniel Moody Director, Ozemantics Pty Ltd, Sydney, Australia

† It is called the “physics” of notations because it focuses on the physical (perceptual) properties of nota-

tions rather than their logical (semantic) properties.

iagramming notations form an integral part of the “language” of IT practice and have done since the earliest be-

ginnings of the field. They are used at all levels of IT practice, from strategic planning down to integrated circuit design. It is hard to think of any area of IT practice where diagramming notations don’t play a central role: for exam-ple, UML in software engineering, BPMN in business process management, PERT charts in project management. They play a particularly critical role in communicating with business stakeholders (end users and customers) be-cause of their ability to present complex ideas in a simple way.

The first IT diagramming notation and ancestor of

all modern IT diagramming notations (c. 1947)

The diagrammatic representation of a model-ling notation (its visual syntax) is arguably its most important characteristic, as this is what notation users and their customers see and di-rectly interact with. It performs a similar role to a graphical user interface for a software sys-tem and has a profound effect on the usability and effectiveness of notations. Human infor-mation processing is highly sensitive to the exact form information is presented: appar-ently minor changes in visual appearance, such as the use of colour, can have dramatic effects on understanding and problem solving performance. For this reason, decisions about the visual representation of notations should be treated with as much care as decisions about their content (i.e. choice of concepts).

Currently, IT diagramming notations are de-signed in a way that has more in common with black magic than reasoned thought. Symbols are defined without any explanation as to why they were chosen or the alternatives consid-ered: the reasons for choosing particular sym-bols are generally shrouded in mystery. There is also a lack of explicit principles for design-ing diagramming notations, with the result that notation designers have to fall back on in-tuition and common sense, which is unreli-able: the effects of graphic design choices are often counterintuitive and our instincts can lead us wildly astray.

As a result, most IT diagramming notations violate some of the most basic principles about how the human visual system works and often act as a barrier rather than an aid to commu-nication, especially with business stake-holders. Also, by using only a limited reper-toire of graphical techniques, they fail to ex-ploit the potential power of diagrams. Some of the most powerful graphical techniques (e.g. spatial location, colour) are rarely, if ever, used in IT diagramming notations.

Diagramming notations play a central role in all engineering and design disciplines, but currently

we lack sound principles for designing them

The goal of this tutorial is to establish a scien-tific basis for diagramming notation design: to help it progress from an art into a science. It defines a set of principles for designing cogni-

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tively effective diagramming notations: nota-tions that are optimised for processing by the human mind. Importantly, the design princi-ples are evidence-based: they are not based on common sense, experience or opinion but on theory and empirical evidence about how our visual systems work. Together they provide a scientific basis for constructing diagramming notations, which has previously been lacking in the IT field.

Semantic Transparency

Visual Expressiveness

Graphic Economy

Dual Coding

Semiotic Clarity

Manageable Complexity

Perceptual Discriminability

Cognitive Fit

Cognitive Integration

The Physics of Notations: evidence-based

principles for designing cognitively effective diagramming notations

The principles have been successfully used to evaluate and improve several modelling nota-tions as well as design notations from first principles. They have recently been proposed as an international standard for designing dia-gramming notations across engineering disci-plines, so could have implications beyond the IT field.

The tutorial challenges some longstanding assumptions about how diagramming nota-tions should be designed and how they have been since the earliest beginnings of the IT field. It identifies serious design flaws in some of the leading notations used in IT practice (e.g. UML, BPMN), together with some simple and practical ways of improving them. It also defines a way of measuring the effectiveness of diagramming notations and for testing them prior to their release (analogous to user accep-tance testing for software systems).

Delivery format The tutorial will be delivered in an interactive manner, with an emphasis on learning by do-ing. A range of practical exercises and exam-ples are used to illustrate the principles and give participants practice in applying them. Examples and exercises feature some of the leading diagramming notations used in IT practice (e.g. UML, BPMN) as well as visual notations from other disciplines.

Learning objectives At the end of the tutorial, participants will be able to: Design diagramming notations in a sys-

tematic, evidence-based manner. Justify choice of symbols with reference to

known principles about how our visual systems work.

Conduct studies to evaluate the usability and effectiveness of notations.

Presenter background Daniel Moody is a Director of Ozemantics, a Sydney-based information management con-sultancy firm. He is recognised as one of Aus-tralia’s leading experts in data modelling and information management and has an interna-tional reputation in these fields. He holds a doctorate in Information Systems from the University of Melbourne and has held senior positions in some of Australia’s leading corpo-rations and consultancy firms. He has con-ducted consulting assignments in 12 different countries, covering a broad range of indus-tries. He has also published over 100 scientific papers, been a keynote speaker 9 times and chaired several international conferences. He was the inaugural President of the Austra-lian Data Management Association (DAMA), former Vice-President on the DAMA International Board and is listed in Who's Who in Science and Engineering. He has lived in 8 different coun-tries, speaks fluent English and can say “hello”, “thank you” and “cheers” in at least 10 different languages.

Structure and content The structure of the tutorial is summarised in the mind map below:

Mindmap of tutorial content

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1. What is a “good” diagramming notation?

This looks at how diagramming notations are used in IT practice and why. It defines what a “good” diagramming notation is (the design goal) and how to measure this.

2. The Art of Diagramming Notation Design: Current Practice

This looks at current practice in designing IT diagramming notations. It analyses some of the leading diagramming notations used in the IT field and practices of the leading notation designers (i.e. what the experts do). The con-clusion is that radical change is needed to cur-rent design practices to produce effective dia-gramming notations.

3. The Theory of Diagramming Notation Design: How Diagramming Notations Communicate

This explains how and why diagramming no-tations communicate, with reference to theo-ries of communication, graphic design, visual perception and cognition. Only by under-standing how diagramming notations com-municate can we improve their ability to communicate. The theory also enables us to explain and predict why some diagramming notations are more effective than others.

4. The Science of Diagramming Notation Design: Principles for Effective Diagramming Notations

This is the main practical content of the tuto-rial, and describes 9 principles for producing effective diagramming notations: Principle of Semiotic Clarity: there should

be a one to one correspondence between concepts and graphical symbols

Principle of Perceptual Discriminability: symbols should be clearly distinguishable from one another

Principle of Semantic Transparency: use symbols whose appearance suggests their meaning

Principle of Complexity Management: in-clude explicit mechanisms for dealing with complexity

Principle of Cognitive Integration: include explicit mechanisms for integrating sepa-rate diagrams together

Principle of Visual Expressiveness: use the full range of visual variables (fully utilise the graphic design space)

Principle of Dual Coding: use text to rein-force and complement graphics

Principle of Graphic Economy: the num-ber of graphical symbols should be cogni-tively manageable

Principle of Cognitive Fit: use different visual representations for different tasks and audiences (visual horses for cognitive courses)

Trade-offs and synergies: understanding interactions among principles

5. Conclusion: A Manifesto for Diagramming Notation Design

This reviews and summarises all the material covered and concludes with a “manifesto” for designing effective diagramming notations.

Intended audience The tutorial is aimed at: Notation designers (e.g. members of OMG

taskforces involved in designing or revis-ing diagramming notations): it defines practical guidelines for constructing effec-tive diagramming notations and improv-ing existing ones.

Tool vendors: it provides the basis for providing enhanced tool support for dia-gramming notations, incorporating ad-vanced graphical capabilities.

Previous presentations This tutorial has previously been presented at some of the most prestigious conferences in the IT field and has received rave reviews from participants (90-100% ratings for both con-tent and presentation quality). These include: International Conference on Model Driven

Engineering Languages & Systems (MODELS: formerly called the UML con-ference)

IEEE International Conferences on Re-quirements Engineering (RE)

International Conference on Business Process Management (BPM)

International Conference on Software En-gineering (ICSE)

IEEE Symposium on Visual Languages and Human Centric Computing (VL/HCC)

International Conference on Advanced In-formation Systems Engineering (CAiSE).

International Conference on Conceptual Modelling (ER)

Australian Software Engineering Confer-ence (ASWEC)

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Sample Slides

The “Physics” of Notations

Towards a Scientific Basis for Designing Visual Notations in Requirements Engineering

1/6: The Nature of Visual Notations

Visual language is one of the oldest forms of knowledge representationVisual language is one of the oldest forms of knowledge representation

Language for the eye

Visual notations form an integral part of the language of IT practiceVisual notations form an integral part of the language of IT practice

Source: Goldstine, H. H., & von Neumann, J. (1947). Planning and coding of problems for an electronic computing instrument. Report prepared for the US Army Ordnance Department.

Unselfconscious design cultureUnselfconscious design culture

Instinct, imitation, tradition

Inability to explain designs

Lack of variety

Source: Alexander, C.W., Notes On The Synthesis Of Form. 1970, Boston, USA: Harvard University Press. 224.

2/6: Current Practice

There must be another way...There must be another way...

“Here is Winnie-the-Pooh coming downstairs, bump,

bump, bump on the back of his head. It is, as far as he knows,

the only way of coming downstairs, but sometimes he

feels that there really is another way, if only he could stop

bumping for a moment to think of it...”

The Design Space (encoding side):The Symbol System of GraphicsThe Design Space (encoding side):The Symbol System of Graphics

Source: Bertin, J. Semiology of Graphics: Diagrams, Networks, Maps. University of Wisconsin Press, Madison, Wisconsin, USA, 1983.

TextureOrientationBrightnessVerticalPosition

ColourSizeShapeHorizontalPosition

RETINAL VARIABLESPLANARVARIABLES

0

90

45o

o

oHighMediumLow

Red Green Blue

Small

Medium

Large

4/6: How Visual Notations Communicate

Perceptual DistortionPerceptual Distortion

Black (0)

White (10)

9

3

7.5

5Finite number of perceptible steps (length)

Infinite range of physical variations

The Physics of Notations:A Theory for Visual Notation DesignThe Physics of Notations:A Theory for Visual Notation Design

Scientific basis for evaluating, comparing, improving, and designing visual notations

Source: Moody, D.L. (2009): The “Physics” of Notations: Towards a Scientific Basis for Constructing Visual Notations in Software Engineering. IEEE Transactions on Software Engineering, December.

Semantic Transparency

Visual Expressiveness

Graphic Economy

Dual Coding

Complexity Management

Cognitive Integration

Semiotic Clarity

Cognitive Fit

Perceptual Discriminability

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1. Principle of Semiotic Clarity1. Principle of Semiotic Clarity

Visual vocabulary (graphical symbols)

Metamodel (semantic

constructs)

C1

C2

C3

C4

symbol redundancy

symbol overload

symbol deficit

symbol excess

?

?

symbolisation mapping (encoding)

denotation mapping (decoding)

Source: Goodman, N. Languages of Art: An Approach to a Theory of Symbols. Bobbs-Merrill Co, Indianapolis, 1968.

5/6: Principles for Visual Notation Design

Semiotic Clarity Analysis Summary (UML)Semiotic Clarity Analysis Summary (UML)

Diagram Type Constr

ucts

Symbo

lsSy

mbo

l red

unda

ncy

Symbo

l ove

rload

Sym

bol e

xces

sSy

mbo

l def

icit

Conte

xtua

l

diffe

rent

iation

Text

ual

diffe

rent

iation

Classes 55 46 15 25 3 29 7 19

Components 4 7 4 4 0 0 3 3

Composite 14 15 3 8 1 7 5 6

Deployments 12 13 4 11 0 3 4 6

Activities 52 33 10 14 1 14 7 4

Interactions 28 16 0 4 0 8 4 4

State Machines 16 21 3 7 2 4 2 6

Use Cases 6 10 3 1 1 0 1 1

Average 26% 46% 5% 35% 20% 30%


Perceptual discriminability in actionPerceptual discriminability in action


Visual DistanceVisual Distance

Number of visual variables on which symbols differ + size of differences (#perceptible steps)

Visualdistance

5/6: Principles for visual notation design

Onomatopoeia: form contentOnomatopoeia: form content


“The Magical Number Seven,Plus or Minus Two”“The Magical Number Seven,Plus or Minus Two”

Human channel capacity or “cognitive bandwidth” limited by working memory capacity

Source: Miller, G. A. (1956). The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information. ThePsychological Review, 63, 81-97.

Cognitive Integration TheoryCognitive Integration Theory

Diagram 1 Diagram 2perceptual integration

conceptual

integration

overall cognitive

map

navigation

between

d iagrams

Source: Kim, J., Hahn, J., & Hahn, H. (2000). How Do We Understand a System with (So) Many Diagrams? Cognitive Integration Processes in Diagrammatic Reasoning. Information Systems Research, 11(3), 284-303.

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1

4

2 65

7

3

80

Visual expressiveness

Non-graphical Visual Saturation

Visual expressivenessVisual expressiveness

Informationcarrying

variables

Free variables(degrees of

visual freedom)


1

4

2 6

5

7

Non-graphical

3

80 Saturation

Visual

expressiveness

Visual Expressiveness of UMLVisual Expressiveness of UML

The Graphic Design SpaceThe Graphic Design Space

HorizontalPosition(x)

Shape

Size

Colour

Brightness

VerticalPosition(y)

Orientation

Texture

5/6: Principles for visual notation design

Colourising diagramsColourising diagrams


Dual CodingDual Coding

Graphics and text should not be enemies


Representation medium (or production method)Representation medium (or production method)

6/6: Conclusion

Notational DarwinismNotational Darwinism

6/6: Conclusion

A Manifesto for Designing Effective Visual Notations

A Manifesto for Designing Effective Visual Notations

OMG tutorial Physics of Notations - Object Management … 1 OMG Technical Conference: Full Day Tutorial The Physics† of Notations: Designing Diagramming Notations That Work Presenter:

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