**Measuring Design Simplicity**

Carlos A.M. Duarte

This recommended process can be used in combination with the checklist provided by ISO/IEC GUIDE 37 (1995) and the checklist can be updated when the ISO guide is refreshed. It is simple, visual and easy to follow. It should help instruction designers especially those new to planning product instructions. It can also contribute to the development of instruction

[1] Agrawala, M.,Doantam, P., Heiser, J., Haymaker, J., Klinger, J., Hanrahan, P., & Ty‐ versky, B. (2003). *Designing Effective Step-By- Step Assembly Instructions*. SIGGRAPH.

[2] British Standards Institution. 2001. BS EN 62079:2001/ IEC 62079:2001. *Preparation of*

[3] Heiser, J., Tyversky, B., Agrawala, M., & Hanrahan, P. 2003. *Cognitive Design Princi‐ ples for Visualizations: Revealing and Instantiating*. 25th Annual Meeting of the Cogni‐

[4] International Organisation for Standardisation. ISO/IEC Guide 37:1995. *Instruction for*

[5] Li,D., Cassidy, T. and Bromilow, D.(2011). *Product Instructions in the Digital Age* In: D. A. Coelho (Ed.) 2011. Industrial Design - New Frontiers. Croatia: InTech. Chapter

[6] Pettersson, R. 2002. *Information design: an introduction.* Amsterdam, Philadelphia: John

[7] Schumacher, P. 2007. Creating effective illustrations for pictorial assembly instruc‐

[8] Sherman, W.R and Craig A. B.2003. *Understanding virtual reality: interface, application,*

[9] Szlichcinski, C. 1984. Factors affecting the comprehension of pictographic instruc‐ tions. In R.S. EASTERBY & ZWAGA, H.J.G.( Ed.), *Information Design* (pp.449–466).

*instructions - Structuring, content and presentation*. Milton Keynes: BSI.

planning tools.

114 Advances in Industrial Design Engineering

**Author details**

**References**

Dian Li, Tom Cassidy and David Bromilow

tive Science Society.

3( p39-p52).

Benjamins Pub. Co

Cichester: Wiley & Sons.

The School of Design at the University of Leeds, UK

*use of products of consumer interest*. Geneva: ISO

tions. *Information Design Journal*, 15(2), pp. 97-109.

*and design*. Amsterdam; London : Morgan Kaufmann.

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54753

**1. Introduction**

From John Maeda (2006) it's clearly known that the study of what is Simplicity is central to Design and Engineering. This chapter deals with this, introducing a method to measure Simplicity.

Design and Engineering are today less an act of drawing or designing something but rather the act of designing a program that in itself conceives a diversity of solutions pertaining to the service or function that we intend to draw or design.

This drawing and designing activity may thus be defined by the creation of new materials; genetic manipulation; software and interface conception; formulation of new forms of languages, mostly those of visualization nature; conception (design) of social, political and cultural ideas; generation of new behaviors with growing complexity.

By opposition and in consequence of complexity and also from the intervention of Design and Engineering we all can access better life quality, we can access better technological artifacts and products while allowing its interaction in a simpler way.

Hence this chapter aims the essence of "simplicity" and how it shows up in several existences, whether it may be in Design, whether it may be in Engineering.

The first time ever someone described how the better organization and functionality of systems can be linked to Simplicity was, in 1870, Claude Bernard (Gene, 2007). However Simplicity, as commonly understood, is not an easy thing to describe, much less to comprehend. What is taken as Simplicity is an undetermined number of concepts to explain what supposedly Simplicity is. The result is a great dispersion that cannot afford reasoning. Some have been able to reduce the given conditions for the existence of Simplicity to ten concepts designated as laws (Maeda, 2006). However we cannot consider it as a definition to describe "simplicity" because such multiplicity is just and only descriptive. If we ought to have a classic image of

the state of the art for Simplicity is we can remember the first knowledge of the relation between triangle sides, which was an in-equation:

$$\mathbf{a} + \mathbf{b} \ge \mathbf{c} \tag{1}$$

and space are measurable. With measure one can add measurement, one can establish

Measuring Design Simplicity http://dx.doi.org/10.5772/54753 117

In 1925, before a set of data, Fisher foresaw the possibility of measurement or calculation of information amount over an unknown variable. A set of data gives an information amount over an incognita that can be measurable or calculated. After Fisher, measuring or calculating the information amount that allows a set of data to acquire uncertainty reducing became a possibility. After Fisher it became possible to know if one is acting upon the incognita,

The method had been established by Jacob Bernoulli back in 1713. In his "The Art of Conjec‐ ture" (*Ars Conjectandi*), he establishes the way to calculate the probability of happening. This probability (*probilitas*) is not the case. It is not a synonymous of *chance*. It is the method of how sure one is about something that is going to happen to the incognita. Bernoulli proposes the method we have selected to present the theory we are about to show, the method of combined

We will increasingly use the results from Melo-Pinto (1998) in the recognition technique (the knowing of what the incognita is) and the mathematic method of combining arguments developed by Dempster and Shafer. They both have defined the set for each argument and its

This chapter establishes that for a given System of Beliefs there will be as much simplicity as the lesser the number of data set elements that will be giving the higher amount of information

It will also be concluded that before a same set of data there will be Systems of Beliefs for which

Hence this chapter is about a measure of Simplicity before a System of Beliefs. Simplicity is as bigger as the smaller the number of elements of the data set that brings the higher quantity of information about the incognita. The relativistic character of Simplicity's measure will be evidenced as well as how to manage it following from the System of Beliefs' properties.

In parallel, it will be established that Design concepts, as well as those of Engineering, have been guiding conception's structuring for Simplicity showing that the concepts expressed in this chapter are not as possible triangles tables were before knowing metrics in Euclid's space,

This principle may be sustained by several applications; particularly through the Universal Principals of Design. It is also built upon arguments or data, as proposed by Lidwell et al. (2010), who stated that Design essence is one of the meanings of the artifact that surround us and that we effectively use in our daily life. Hence, we will demonstratehow Design Simplicity

Following Claude Bernard, who in 1870 discovered physiologic medicine and stated that *the condition for a free and independent life lies in the stability of the internal mean*, which naturally depends on the wellbeing of each individual and is built under his own system of beliefs.

there will be higher concentration of information about the incognita.

comparisons; one can recognize solutions, and the future can be sound.

guessing, predicting or foretelling.

weight as a function in the System of Beliefs.

argumentation.

about the incognita.

but rather a metric for Simplicity.

is also an Engineering parameter.

In-equations have an infinite number of solutions. For millenniums solutions were published with possible triangles. The amount of three side set measures could close in a triangle. So it was until Pythagoras simplicity:

$$\mathbf{a}^2 + \mathbf{b}^2 = \mathbf{c}^2 \tag{2}$$

As equations have a finite number of solutions never again was it necessary to write down tables for possible triangles. The comprehension of real space metrics brought up the great growing efficiency to those who design structures. The solution for the problem of knowing if three given measures of line segments would originate a triangle is said to get simplified, and metrics allow simplicity.

Just as in the time when one could only know that the addition of two sides of a triangle was bigger or equal to the length of the third side, to find the solution for simplicity we can also, today, establish tables.

One of the most recent (2006) is that of Maeda. It functions as a synthesis proposal in the rules of Simplicity built in ten laws judged by being different and independent from each other.

This chapter aim is to present a measure for simplicity that will turn it into a parameter central to Design and Engineering.

Until now there are a certain number of rules or laws for Simplicity. The most recent attempt to reduce diversity of notions, Maeda (2006) defines ten laws. But every time we arrive at number ten we cease the main question again. Why ten? Why not eleven or nine? Maeda and his theory of Simplicity suffer from the fact of not having been brought to the Science domain, meaning it has not been made measurable.

Thus this chapter's object is also to clarify Information's concepts, taken as data synonymous, stated arguments and rarely faced as Science parameters, either in Design or Engineering, so thus measurable, though observer dependent and relativistic.

In this context, the chapter is meant to suggest, until designers find out about it, that Simplicity can be measurable and can be so from Fisher's Information Amount (1925) definition. At the same time, the notion will come by that simplicity's measure is also relativistic yet measurable, thus "mathematizable", using concepts initiated by Jacob Bernoulli and those more recently funded in mathematics by Dempster and Schafer (1978).

In 1925, Fischer, upon realizing that just as space and time, information is something we all know until someday someone asks us about it. Yet he also knew that physical language description is based in the fact that, whether or not gathering knowledge of its essence, time and space are measurable. With measure one can add measurement, one can establish comparisons; one can recognize solutions, and the future can be sound.

the state of the art for Simplicity is we can remember the first knowledge of the relation between

In-equations have an infinite number of solutions. For millenniums solutions were published with possible triangles. The amount of three side set measures could close in a triangle. So it

As equations have a finite number of solutions never again was it necessary to write down tables for possible triangles. The comprehension of real space metrics brought up the great growing efficiency to those who design structures. The solution for the problem of knowing if three given measures of line segments would originate a triangle is said to get simplified,

Just as in the time when one could only know that the addition of two sides of a triangle was bigger or equal to the length of the third side, to find the solution for simplicity we can also,

One of the most recent (2006) is that of Maeda. It functions as a synthesis proposal in the rules of Simplicity built in ten laws judged by being different and independent from each other. This chapter aim is to present a measure for simplicity that will turn it into a parameter central

Until now there are a certain number of rules or laws for Simplicity. The most recent attempt to reduce diversity of notions, Maeda (2006) defines ten laws. But every time we arrive at number ten we cease the main question again. Why ten? Why not eleven or nine? Maeda and his theory of Simplicity suffer from the fact of not having been brought to the Science domain,

Thus this chapter's object is also to clarify Information's concepts, taken as data synonymous, stated arguments and rarely faced as Science parameters, either in Design or Engineering, so

In this context, the chapter is meant to suggest, until designers find out about it, that Simplicity can be measurable and can be so from Fisher's Information Amount (1925) definition. At the same time, the notion will come by that simplicity's measure is also relativistic yet measurable, thus "mathematizable", using concepts initiated by Jacob Bernoulli and those more recently

In 1925, Fischer, upon realizing that just as space and time, information is something we all know until someday someone asks us about it. Yet he also knew that physical language description is based in the fact that, whether or not gathering knowledge of its essence, time

a + b c ³ (1)

2 22 a + b = c (2)

triangle sides, which was an in-equation:

was until Pythagoras simplicity:

116 Advances in Industrial Design Engineering

and metrics allow simplicity.

today, establish tables.

to Design and Engineering.

meaning it has not been made measurable.

thus measurable, though observer dependent and relativistic.

funded in mathematics by Dempster and Schafer (1978).

In 1925, before a set of data, Fisher foresaw the possibility of measurement or calculation of information amount over an unknown variable. A set of data gives an information amount over an incognita that can be measurable or calculated. After Fisher, measuring or calculating the information amount that allows a set of data to acquire uncertainty reducing became a possibility. After Fisher it became possible to know if one is acting upon the incognita, guessing, predicting or foretelling.

The method had been established by Jacob Bernoulli back in 1713. In his "The Art of Conjec‐ ture" (*Ars Conjectandi*), he establishes the way to calculate the probability of happening. This probability (*probilitas*) is not the case. It is not a synonymous of *chance*. It is the method of how sure one is about something that is going to happen to the incognita. Bernoulli proposes the method we have selected to present the theory we are about to show, the method of combined argumentation.

We will increasingly use the results from Melo-Pinto (1998) in the recognition technique (the knowing of what the incognita is) and the mathematic method of combining arguments developed by Dempster and Shafer. They both have defined the set for each argument and its weight as a function in the System of Beliefs.

This chapter establishes that for a given System of Beliefs there will be as much simplicity as the lesser the number of data set elements that will be giving the higher amount of information about the incognita.

It will also be concluded that before a same set of data there will be Systems of Beliefs for which there will be higher concentration of information about the incognita.

Hence this chapter is about a measure of Simplicity before a System of Beliefs. Simplicity is as bigger as the smaller the number of elements of the data set that brings the higher quantity of information about the incognita. The relativistic character of Simplicity's measure will be evidenced as well as how to manage it following from the System of Beliefs' properties.

In parallel, it will be established that Design concepts, as well as those of Engineering, have been guiding conception's structuring for Simplicity showing that the concepts expressed in this chapter are not as possible triangles tables were before knowing metrics in Euclid's space, but rather a metric for Simplicity.

This principle may be sustained by several applications; particularly through the Universal Principals of Design. It is also built upon arguments or data, as proposed by Lidwell et al. (2010), who stated that Design essence is one of the meanings of the artifact that surround us and that we effectively use in our daily life. Hence, we will demonstratehow Design Simplicity is also an Engineering parameter.

Following Claude Bernard, who in 1870 discovered physiologic medicine and stated that *the condition for a free and independent life lies in the stability of the internal mean*, which naturally depends on the wellbeing of each individual and is built under his own system of beliefs. Simplicity is also related to a system of beliefs, and as such it will always be associated to the on-looker that applies it or observes it. Hence one can state that "Simplicity" is relativist, once it's System of Beliefs' are dependable and that variants from the same System of Beliefs can be understood as a School. It will suffice that a set of designers or engineers share the same arguments for each one of them as well as the same weight.

share it, confirm it by the Holly Readings and with reasoning, the preacher should always use, if possible always with examples and rejecting contradictory arguments, hence he might be

Measuring Design Simplicity http://dx.doi.org/10.5772/54753 119

It is this persuasion capacity that by nature is present in human life through different degrees

But what is effectively Simplicity? Having also apprehended how really complicated it is to establish a measure of Simplicity, Maeda (2006) was able to describe Simplicity in ten (chapters)

**•** To reduce – the simpler way to achieve simplicity is by means of a conscious reduction;

Still according to Maeda, simplifying a design is harder than making it complicated. The great majority of examples he uses are the result of experiences and problems he underwent.

However his considerations about simplicity in life, in business, in Technology or in Design or Engineering, are not to be considered as having been obtained in the basis of a method from

As well as we do not consider a science that same method of gathering the catalog of squared

It finds out that, as to the meanings of simplicity, we are allowed an infinite variety of data, and as such the information we have is still short, so being before an in-equation as it has an

In this chapter we will be led to know, as Pythagoras did through his theorem, that there is also a way that allows us to be objective, measuring, on the contrary of the description from

**•** To organize – organization makes a system of many look like a system of few;

**•** Context – what lies in the simplicity's periphery is definitely non peripheral;

**•** Singleness – simplicity is to subtract the obvious and to add meaning.

**•** Distancing – more seems like less simply by going far, far away;

angles registration that we referred in the framework of this chapter.

able to conclude and persuade…

laws:

and combinations that allies simplicity and complexity.

**•** Differences – simplicity and complexity need one another;

**•** Time – time economy transmits simplicity; **•** Learning – knowledge simplifies everything;

**•** Emotions – more emotions is better than less;

**•** Failure – some things may never be simple;

Then he adds three more components, which are:

**•** Confidence – in simplicity we trust;

**•** Opening – opening means simplicity;

**•** Energy – use less, win more.

infinite number of solutions.

a scientific nature.
