Data
Principles for creating GOV.UK-branded charts and visualisations.
Data visualisation is the graphic representation of data. We use visual elements, such as lines, shapes and colours, to convey information to users.
Visualising data can help communicate information that may otherwise be lost due to complexity.
Showing these details in a clear and easy to understand way allows users to understand information quickly and confidently. This helps inform users and equip them to make relevant decisions.
Principles
When creating visualisations for GOV.UK, we follow these principles.
1. Clarity
By understanding user needs, we provide only the relevant information and reduce unnecessary complexity. We use a visual hierarchy, consistent labelling and align with the core brand to maintain clarity.
2. Accessibility
We’re committed to providing everyone access to the same content. We avoid using colour alone to convey information, use appropriate text contrast ratios and provide alternative versions of the same data.
3. Accuracy
We take great care to ensure visualisations are true and accurate representations of the underlying data. This includes showing data along consistent intervals with a baseline that starts at zero where appropriate. We aim to cite sources and provide supporting information.
4. Consistency
A consistent approach to data visualisation enhances clarity, accessibility, and accuracy. Consistency allows users to gain familiarity and improve their understanding.
5. Engagement
Our principles and core brand allow us to create visualisations that are relevant, engaging and memorable. So users are more informed when they need it most.
Convey a clear narrative to users
When creating visualisations for GOV.UK, we ensure that we keep a few things in mind.
1. We know its purpose
Before starting, take the time to clearly define the purpose of the visualisation.
Understanding user needs and their level of expertise on the subject will guide design decisions. It will also help ensure the story you’re telling with data is both meaningful and effective with users.
2. We know the story
Effective data visualisation is about storytelling and communicating insight. Structure visuals to tell a story and support the overarching narrative.
3. We know what is important
Avoid overwhelming users with too much information. Strip away unnecessary distractions and prioritise information with a focus on clarity and accessibility.
Selecting a visualisation type
Different visualisation techniques are better suited for different types of data and messages. Choosing which one to use will depend on the:
- message conveyed
- statistical relationships within the data
- target audience
The table below, originally produced by ONS Analysis Function, provides examples of different statistical relationships. It also suggests the type of chart that would work best for a specific example.
| Relationship | Example | Recommended chart types |
|---|---|---|
| Distribution | Population by age | Bar chart, population pyramid, box plot, dot plot |
| Time | Price inflation over time | Line chart, calendar heat map |
| Rank | Schools ranked by performance | Bar chart, lollipop chart, slope chart |
| Deviation | Rail company performance compared with target | Bar chart, dot plot |
| Correlation | Relationship between weight and height | Scatterplot, line graph |
| Magnitude | Average income by region | Bar chart |
| Spatial | Geographical clusters of notifiable diseases | Map |
| Part-to-whole | Total economic production by industrial sector | Pie chart, donut chart, tree map, bubble chart |
| Flow | Trade between countries | Sankey graph |