Datavisual anatomy

The elements that make up a data visualization

𝗔𝗻𝗮𝘁𝗼𝗺𝘆 𝗼𝗳 𝗗𝗮𝘁𝗮 𝗩𝗶𝘀𝘂𝗮𝗹𝘀

During my time at the Design Academy Eindhoven, one phrase was often echoed by the teachers: “Designing is making choices.”

10 years later I find that this wisdom rings especially true in the realm of data visualization. With countless possibilities, the challenge often lies not in what to add, but in what to leave out.

Creating effective data visualizations is a journey of decision making. From data selection, visual type, axis titles and tooltips, to error bands and dynamic formatting. The options seem overwhelming. Yet it are these very choices that shape the anatomy of your data visuals. Each element, carefully considered or consciously omitted, contributes to a clearer, more impactful story.

𝗦𝗼 𝘄𝗵𝗲𝗿𝗲 𝘁𝗼 𝘀𝘁𝗮𝗿𝘁?

Understanding the function of the different visual elements is essential, both for creating and interpreting data visualizations. It empowers you to make informed choices that align with desired outcomes. Moreover, a solid understanding of visual anatomy streamlines collaboration with co-creators, making discussions more productive and insightful.

In this guide, I break down the most common data visual elements and what their use is. For each element you should make deliberate choices about visibility, colour, size and where needed wording.

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𝗨𝘀𝗲 𝘁𝗵𝗲 𝗮𝗻𝗮𝘁𝗼𝗺𝘆 𝗶𝗻 𝟯 𝘄𝗮𝘆𝘀:

1.     𝘋𝘪𝘴𝘱𝘭𝘢𝘺𝘪𝘯𝘨 𝘪𝘯𝘧𝘰𝘳𝘮𝘢𝘵𝘪𝘰𝘯
Presenting your data effectively is the cornerstone of any visualization. This involves using charts, graphs, and maps to convey your message clearly. The development effort here is significant, as this is the core of your data visualization design. All other elements, such as labels, colors, and annotations, are there to support the information display and enhance understanding. Think of it as building a house: the structure (your data) needs to be solid before you can add the finishing touches.

Elements: x and y axis, data plot (lines, bars etc), error bars

2.     𝘎𝘶𝘪𝘥𝘪𝘯𝘨 𝘪𝘯𝘵𝘦𝘳𝘱𝘳𝘦𝘵𝘢𝘵𝘪𝘰𝘯
Helping your audience understand what they see is crucial. This means paying attention to units, quantities, and categories. Clear axis titles, legends, and tooltips can make a world of difference. These elements guide your audience through the data, ensuring they grasp the insights you’re presenting. It’s like being a tour guide in a museum, where your explanations help visitors appreciate the exhibits.

Elements: legend, axis titles, axis labels, gridlines, marker

3.     𝘗𝘳𝘰𝘷𝘪𝘥𝘪𝘯𝘨 𝘤𝘰𝘯𝘵𝘦𝘹𝘵
Context is what turns raw data into a compelling story. Consider factors like time, location, and other relevant details that can provide deeper insights. Contextual elements enhance the storytelling aspect of your visualizations, making them more relatable and meaningful. Imagine reading a novel without any background information on the characters or setting – it would be much harder to connect with the story. Similarly, providing context in your data visuals helps your audience connect with the information on a deeper level.

Elements: title, subtitle, tooltips, data labels

Conclusion

Mastering the anatomy of data visuals is a journey of continuous learning and refinement. By understanding and thoughtfully applying the various elements of data visualization, you can transform raw data into compelling stories that resonate with your audience. Remember, the power of a great data visualization lies not just in the data itself, but in how you choose to present it.

Embrace the process, experiment with different approaches, and most importantly, enjoy the creative journey!