Data Visualisation: A Handbook for Data Driven Design

by Andy Kirk

Not all charts that use bars necessarily need to start from a zero origin. Variations in the use of the waterfall chart, for example, might be used to show quantitative changes or differences between absolute values (the ‘delta’).

Legitimate outliers will potentially distort your ideal scale choices but will need to be accommodated somehow in the space you are working with.

One solution for dealing with this is to use a non-linear logarithmic (often just known as a ‘log’) scale.

Unity in composition provides a similar sense of harmony and balance between all objects. The flow of content should feel logical and meaningful.

‘I’m obsessed with alignments. Sloppy label placement on final files causes my confidence in the designer to flag.

The enduring idea that elegance in design is most appreciated when it is absent is just as relevant with composition.

Do not be afraid to use empty space more extensively across larger regions as a device to create impact.

Let’s learn more about the specific components of the development cycle. As mentioned, the consequence of the previous five chapters of this book led to completion of the first step, ‘developing a concept design specification’, which would have entailed creating initial storyboards and/or wireframes to capture what you intend to create. So what follows this?

The respective terms tend to be used interchangeably but I feel mock-up is more applicable for developing static work, whereas prototype is more relevant to interactive work.

Trustworthy design testing concerns assessing the reliability of the work, in terms of the integrity of its content and performance.

Accessible design testing relates to how intuitive or sufficiently well explained the work is.

You do not want to get feedback when it is too late or change is expensive.

Troubleshooting is one characteristic of this stage, as too is editing, which is more aligned with fine-tuning than problem solving.

stripping away superfluous content;

In any creative process a visualiser is faced with having to declare work complete. Judging this can be quite a tough call to make.

often it comes down to a fingertip sense of when you feel you are entering the period of diminishing returns – when the refinements you make no longer add sufficient value for the amount of effort you invest in making them.

‘You know you’ve achieved perfection in design, not when you have nothing more to add, but when you have nothing more to take away.’ Antoine de Saint-Exupéry, Writer, Poet, Aristocrat, Journalist and Pioneering Aviator

A visualisation may not have every feature you could possibly want, but if it gets the message across and is useful to people, it’s good enough.

Are you ready?

Communicating your work is a big deal.

What ongoing commitment exists to support the work?

Measuring the effectiveness of a data visualisation from an outcome perspective remains an elusive task. This is largely because it can only be determined according to contextual measures of success. This is why defining ‘purpose’ is necessary early on.

It is a journey that never stops because data visualisation is a subject that has no ending.

[but] there is this gap and for the first couple of years that you’re making stuff, what you’re making is just not that good … It’s trying to be good, it has potential, but it’s not. But your taste, the thing that got you into the game, is still killer. And your taste is why your work disappoints you. A lot of people never get past this phase, they quit. Most people I know who do interesting, creative work went through years of this.