Data Visualisation Strategy - Data Viz Checklist

Creating high-impact visualisations can seem like a daunting task. Straying from what analytical software provides out of the box is to wander into terra incognita for some. Do I use the stock standard blue and orange line graph supplied by Excel, or do I mix in some personality to these graphs? I want some more colour, some more interaction, some more pizazz! But how do I do this?

You're in luck. There is a checklist available to us courtesy of the brilliant minds of Stephanie Evergreen and Ann Emery.

Download the checklist here.

Text

The checklist stipulates that text be used sparingly. The driving force behind visualisation moves away from using text in a raw format. Any text outside the following must pack a punch or be removed.

• 6–12-word descriptive title is left-justified in the upper left corner.
• Subtitles and annotations provide additional information.
• Text size is hierarchical and readable.
• The text is horizontal.
• Data is labelled directly.
• Labels are used sparingly.

Arrangement

Ensuring that data points and visual elements are presented and organised is critical for successful data visualisation. The correct arrangement helps viewers comprehend the information more quickly, while incorrect placement can result in confusion or misunderstanding. Consequently, the proper interpretation of graph elements is essential for successful visualisation.

• Proportions are accurate.
• Data are intentionally ordered.
• Axis intervals are equidistant.
• The graph is two-dimensional.
• The display is free from decoration.

Colour

Choosing a colour for a design or print can be tricky, as certain colours have specific cultural connotations and meanings. For example, red is often associated with passion, while blue is thought to represent loyalty. To ensure you choose the right colour, use tools such as Color Brewer that provide elaborate colour schemes suitable for colour printing and colourblind people.

• The colour scheme is intentional.
• Colour is used to highlight critical patterns.
• The colours are legible when printed in black and white.
• Colour is legible for people who are colourblind.
• Text sufficiently contrasts the background.

Lines

Lines, such as gridlines, borders, tick marks, and axes, can often make a graph more cluttered and difficult to interpret. Therefore, whenever possible, any unnecessary lines should be removed to improve the readability of the data.

• Gridlines, if present, are muted.
• The graph does not have a borderline.
• Axes do not have unnecessary tick marks or axis lines.
• The graph has one horizontal and one vertical axis.

Overall

When visualising data, it is essential to ensure that only the most critical information is presented via graphs. Non-essential information can lessen the impact of visualisation; therefore, it is crucial to focus on what truly needs attention. This will ensure that charts can help catch the viewer's eye and convey information effectively.

• The graph highlights significant findings or conclusions.
• The type of graph is appropriate for data.
• The graph has an appropriate level of precision.
• Individual chart elements work together to reinforce the overarching takeaway message.

How well are your visualisations scoring on the DataViz checklist?

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