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How can you make data visualization software accessible for diverse users?

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Data visualization software can help you communicate complex data in engaging and interactive ways. But not everyone can access or use your data visualizations equally. To make your data visualization software accessible for diverse users, you need to consider some key factors and best practices. In this article, we will explore how you can improve the accessibility of your data visualization software by following these six steps:

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1 Understand your users

The first step to make your data visualization software accessible is to understand who your users are and what their needs and preferences are. You can use user research methods, such as surveys, interviews, personas, and user testing, to gather insights about your users' backgrounds, goals, challenges, and expectations. You can also use accessibility guidelines, such as the Web Content Accessibility Guidelines (WCAG), to identify the common barriers and requirements for different types of users, such as those with visual, auditory, cognitive, or motor impairments.

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2 Choose the right format

The second step to make your data visualization software accessible is to choose the right format for your data and your message. Depending on the type and complexity of your data, you can use different formats, such as charts, graphs, maps, tables, or diagrams, to convey your information. You should also consider the context and purpose of your data visualization, and how it will be displayed and consumed by your users. For example, if your data visualization is meant to be viewed on a mobile device, you should avoid using too many details or elements that can clutter the screen or require zooming or scrolling.

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Craig Rothe

I help IT leaders unlock transformative data insights within 30 days
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Choosing the best visual type and format is easier if you truly understand and know the users. That is the previous point made in this article. Knowing the “who?” is important here. Some users prefer interactive visuals, others prefer static grids (hello Finance). And some users despise heat maps. In my experience, mobile users are still a bit scarce, but that capability is powerful and forces new design decisions.

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3 Use clear and consistent design

The third step to make your data visualization software accessible is to use clear and consistent design principles and elements. You should use colors, fonts, shapes, icons, labels, and legends that are easy to see, read, and understand by your users. You should also avoid using colors or patterns that can cause confusion or discomfort, such as red-green color blindness or flashing effects. You should also use contrast, alignment, hierarchy, and whitespace to create a visual structure and balance that guides your users' attention and comprehension.

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Yiren Wang

Data Visualization Designer | Product Designer
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In my opinion, it is also important to consider general users - for instance, to help people with color blindness, it is recommended to use patterns instead of colors to distinguish classes, which might actually be less recognizable for people without color difficulties. Thus, we should allow users to choose the format they want to view, for instance, a toggle for color OR pattern mode.

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4 Provide alternative and supplementary information

The fourth step to make your data visualization software accessible is to provide alternative and supplementary information for your data and your visuals. You should use captions, titles, descriptions, and summaries to explain the main points and insights of your data visualization. You should also use text alternatives, such as alt text, captions, transcripts, or audio descriptions, to provide equivalent information for users who cannot see or hear your visuals. You should also use interactive features, such as tooltips, filters, or annotations, to allow your users to explore and customize your data visualization according to their interests and needs.

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Yiren Wang

Data Visualization Designer | Product Designer
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Adding captions or alternative texts is not only helping users who have difficulties viewing the visuals. It might also help people who has total blindness. We should consider what format of alternative texts can and cannot be read by screen-readers. For instance, tooltips is usually not able to be recognized by screen readers. In addition, we should consider alternatives for hovering features - a simple click is much more accessible for users with motion difficulties, who might not be able to use mouses as their interaction devices. Of course, we should also make this as an optional feature.

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5 Test and evaluate your accessibility

The fifth step to make your data visualization software accessible is to test and evaluate your accessibility level and performance. You should use accessibility tools, such as validators, checkers, or simulators, to identify and fix any errors or issues in your code or design that can affect your accessibility. You should also use user feedback, analytics, or usability testing to measure and improve your user satisfaction and engagement. You should also follow the accessibility standards and best practices, such as the WCAG, to ensure your compliance and quality.

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6 Keep learning and improving

The sixth and final step to make your data visualization software accessible is to keep learning and improving your skills and knowledge. You should stay updated with the latest trends and developments in data visualization and accessibility. You should also seek inspiration and guidance from other data visualization experts and examples. You should also be open to feedback and suggestions from your users and stakeholders. You should also be willing to experiment and iterate with different data visualization techniques and tools.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can you make data visualization software accessible for diverse users?

1

2

3

4

5

6

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1 Understand your users

2 Choose the right format

3 Use clear and consistent design

4 Provide alternative and supplementary information

5 Test and evaluate your accessibility

6 Keep learning and improving

7 Here’s what else to consider

Data Visualization

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How can you make data visualization software accessible for diverse users?

1

2

3

4

5

6

7

1 Understand your users

2 Choose the right format

3 Use clear and consistent design

4 Provide alternative and supplementary information

5 Test and evaluate your accessibility

6 Keep learning and improving

7 Here’s what else to consider

Data Visualization

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