Accessible data visualisation

Data visualisation is a powerful way to spot patterns and trends in data, tell stories with data and turn raw data into actionable insight. However, to maximise the benefits of data visualisation we need to ensure that it is accessible to our intended audience. After spending significant amounts of time cleaning, prepping, analysing and visualising a dataset, you want it to be seen and understood by as many people as possible.

Accessibility can range from ensuring that audiences have access to the right software to view the visualisation to ensuring our maps and visualisations are optimised for those with colour vision deficiency. As cartographers and data visualisation designers, we need to think carefully about accessibility and remove as many barriers as possible. This is a key part of the design process and often requires thought before you even start to make your map or data visualisation.

Although there aren’t specific regulations for creating accessible data visualisations, a good place to start for general advice and principles relating to accessibility are the Web Content Accessibility Guidelines (WCAG).

Colour

Colour has a big impact on accessibility, particularly with regard to those who have a form of Colour Vision Deficiency (often known as colour blindness). Almost 10% of the population in the UK have some form of CVD, so it’s an important consideration. We discuss the types of CVD and implications for design and how this can be addressed fully in our section on colour.

One simple way of increasing accessibility for those with CVD is to use patterns or symbols in addition to colour to help distinguish between features. Don’t rely on a colour difference alone to distinguish between feature or prompt a response or action. This could simply be adding a tree fill to woodland areas and a marsh symbol to marshland.

Another way to make your data visualisation accessible, related to colour, is ensuring sufficient contrast between features and also between symbols/text and the background. It is this contrast which makes your visualisation legible and understandable. The WCAG recommend a minimum contrast ratio of 4.5:1.

Labelling and Descriptive Text

Adding labels to your data visualisation is a great way to improve accessibility. Not only does it reduce the reliance on visually perceiving differences in colour but can also add much needed explanation to those who are not familiar with the subject you are visualising.

When adding labels, it’s also important to think about their legibility in terms of contrast with the background, size and placement. We discuss the function of labels and how to make them legible in significant depth in our section on text.

For both printed and online content, a title and short description of the take-away message of your data visualisation can often help those who have CVD, other visual impairments or are neurodiverse to understand your visualisation. If designing for an online audience, you might want to consider providing some alternative text alongside your visualisation to help those who use screen readers to understand the message of your visualisation.

Access to software and cost implications

To ensure our data visualisations are as accessible to the target audience as they can be, it’s worth thinking carefully about the software that you create it in and format you then publish it in. Do people need a specific piece of software or a specific licence or account to view your data visualisation? If they do, is there a cost implication? Could you produce your data visualisation in a different way to remove these barriers?

Other accessibility considerations

Although colour and the use of labelling are great for those who suffer with CVD, there are many other accessibility considerations, such as those who are neurodiverse or have physical disabilities. For example, some major mapping platforms have developed maps which can be used by those who struggle to make precise mouse clicks. They allow users to click in a vague area and then use a screen reader or keyboard shortcuts to select the feature they want. To cater better for those who are neurodiverse, try to keep your data visualisation simple and remove any unnecessary information. A further consideration for accessibility is the technical literacy of the audience and level of knowledge and understanding on the topic you’re visualising.

Bringing it all together…

Another nice example of increasing accessibility is the work done by Ordnance Survey in collaboration with British Cycling in Birmingham. In early 2023, British Cycling published a set of cycle routes on OS Maps aimed at encouraging people from disadvantaged backgrounds to get out on their bikes and explore the green spaces around Birmingham – improving physical and mental wellbeing. However, not everyone has access to a smartphone and not everyone can afford an OS Maps subscription. So, to increase accessibility, specially designed printed maps have been created which can either be downloaded and printed at home or picked up for free at specific sites around the city. These maps do not need a specific software to view them, they do not need a subscription and have a simple playful design, aimed at novice map users. They also use a CVD friendly colour pallet! You can view and download the maps here.