We have come to the end of our Data Design Principles series. In this final post, let’s ask the most basic question – what exactly is data viz? (ha, rhyme intended)
Simply put, data visualisation compares multiple values and puts the information into context. The process comes in two steps:
- Discover: the collection and organisation of data
- Communication: the planning and delivery of a communication strategy to communicate the data to target audience
“Of all methods for analysing and communicating statistical information, well-designed data graphics are usually the simplest and at the same time the most powerful.”
– Edward Tufte
The human brain has been dubbed a “pattern recognition machine”. Good dataviz should be understandable, memorable and actionable. For designers, it is crucial to simplify the data, so it’s easier to translate it to something visual that viewers can understand and decipher without issue.
There are some tricks to making your dataviz understandable and memorable, that is, by using repetition, alignment and symmetry to your advantage.
1. Using repetition
Repetition is not repeating the exact same visual elements throughout a design, but more so reusing similar elements to make a cohesive piece of work. For some design work that is complex, like dataviz, using repetition will create a sense of unity and consistency, strengthening the design.
Some say that repetition in design is a sort of brainwashing – that the more people see it, the more they will be familiar with it, thus remember it better. It is human nature to be attracted to familiarity.
In communicating data, repetition can be reflected through using similar chart types, shapes or colours in the design. By using repetition, designers are non-verbally creating an association between the elements, communicating to the viewers that the different content are related to one another.
An example of colour combination repetition.
An example of repetition through shapes.
Alignment refers to lining up the graphic elements in a type of grid — either vertically or horizontally.
Horizontal alignment includes:
- Flush-left → reference point is the left margin
- Flush-right → reference point is the right margin
- Centered → reference point is an imaginary line in the middle of the page
- Fully justified → aims for smooth justification on all the margins, also called forced justification.
With vertical alignment, the rules are pretty much the same but in a vertical sense – either top, bottom or middle (center).
So why would we need grids? Well, we don’t actually need it, but it aids in the placement of text and graphics on a design.
Our brains are wired to love symmetry — we get a certain satisfaction when things are in order and organised. In design, symmetry offers an ordered approach, making viewers find elements more readily. This is also called balance. There are two different ways of achieving balance:
1. Formal balance
Used in very simple and specific layouts with little use elements. This is when the design has a very specific objective. For example, the design of Google’s homepage utilises formal balance. If Google had a busy-looking main page, users might get distracted when wanting to research something – which defeats the purpose of Google as a search engine.
2. Informal balance
This type of balance accepts a certain level of asymmetry in the design, albeit with a recognisable genuine effort to assert balance of content on either side of the vertical/horizontal axis. Thus, the designer isn’t constrained to keep a strict symmetry, yet still tries to utilise the rules of balance and insert a somewhat even distribution of elements.
We hope you’ve been enjoying the Data Design Principles Series.
Keeping repetition, alignment and balance in mind will make your designs stronger and more aesthetically pleasing. These design principles are just guidelines, though. Good designers shouldn’t be afraid to go their own way, following their own instincts.
Now go forth and design!