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Understandable
Understandable
Ensure users can easily understand and interpret your visualizations and dashboards.
Accessible visualizations should be clear, predictable, and easy to interpret. Users should be able to understand what a visualization shows, how to interact with it, and what conclusions can reasonably be drawn from the data. Thoughtful design choices can reduce confusion, improve comprehension, and support users with a wide range of experiences, backgrounds, and cognitive needs.
The guidance in this section focuses on three key aspects of understandability: Clean & Simple Layout, Plain Language & Labels, and Consistency & Cognitive Load. Together, these practices help users locate information, interpret findings, and interact with visualizations more confidently and efficiently.
Clean & Simple Layout
Clean & Simple Layout
Why It Matters
Why It Matters
When too much information is presented at once, users may struggle to identify key insights and understand relationships within the data. Clean, intentional layouts reduce visual clutter and help users focus on the information that matters most.
What to Avoid
What to Avoid
Overcrowded dashboards or visualizations.
Multiple chart types and scales within a single figure.
Excessive colors, borders, or decorative elements.
Poor alignment or inconsistent spacing.
Hiding key information among secondary details.
Presenting too many metrics simultaneously.
What Good Looks Like
Related information is grouped together.
Visual hierarchy guides users through the content.
Adequate whitespace separates elements.
Charts focus on a single purpose or message.
Unnecessary visual elements are removed.
Key insights are easy to identify quickly.
Example: Simplifying a Complex Visualization
Example: Simplifying a Complex Visualization
The example below demonstrates how reducing visual clutter and focusing on a single message can make visualizations easier to understand. Separating unrelated measures into multiple charts helps users identify important trends more quickly and with less effort.
Before: Less Accessible
Accessibility Challenges
Multiple metrics compete for attention within a single chart.
Users must interpret data across multiple scales and axes.
A generic title provides limited guidance about the key takeaway.
Visual clutter makes important trends more difficult to identify.
The chart attempts to communicate several messages simultaneously.
After: More Accessible
Accessibility Improvements
Headline-style titles help users identify key insights quickly.
Each visualization communicates a single, focused message.
Multiple scales and competing axes have been removed.
Related measures are grouped together while unrelated measures are separated.
Simplified chart designs make trends easier to compare and interpret.
Quick Test: Can a first-time viewer identify the primary takeaway of the visualization within five seconds? If not, consider simplifying the layout or separating unrelated information into multiple visualizations.
Resources: Clean & Simple Layout
Resources: Clean & Simple Layout
These tools and resources can help you reduce visual clutter, establish clear hierarchy, and organize information in ways that make visualizations easier to understand.
General Guidance
Highcharts: 10 Guidelines for Data Visualization Accessibility: Practical recommendations for simplifying visualizations and improving readability and interpretation.
Oregon Health Authority: Accessible Data Visualization Quick Guide: Comprehensive guidance for creating clear, accessible visualizations and dashboards.
UMass President's Office: Create Accessible Data Visualizations: Recommendations for designing visualizations that are easier to understand and interpret.
Reducing Cognitive Load
A11Y Collective: The Ultimate Checklist for Accessible Data Visualizations: Includes practical recommendations for reducing complexity and improving user comprehension.
Pope Tech: How to Make Charts and Graphs More Accessible: Guidance on creating simpler, more understandable visualizations and reducing unnecessary complexity.
Design Systems & Examples
U.S. Web Design System: Data Visualizations: Provides examples and design guidance for creating clear and understandable visualizations.
Harvard: Data Visualizations, Charts, and Graphs: Best practices for creating visualizations that communicate information clearly and efficiently
Additional Reading
Johns Hopkins: Data Visualizations for Everybody: Presentation slides introducing accessible and understandable visualization design principles.
Seeing with Words: An Intern's Introduction to Accessible Infographics: Reflection on making information graphics easier to interpret and understand.
Plain Language
Plain Language
Why It Matters
Why It Matters
Even when text is readable, it may not be understandable. Titles, labels, annotations, and filters that rely on jargon, acronyms, or specialized terminology can create barriers for users who are unfamiliar with institutional language. Plain language helps users focus on understanding the data rather than decoding terminology.
What to Avoid
What to Avoid
Internal jargon and specialized terminology.
Unexplained acronyms and abbreviations.
Technical language that assumes subject-matter expertise.
Ambiguous or generic chart titles.
Titles that describe the chart but not its significance.
Inconsistent terminology across visualizations.
What Good Looks Like
What Good Looks Like
Use familiar, audience-centered language.
Spell out acronyms when needed.
Explain specialized terminology.
Choose descriptive titles that provide context.
Use consistent terminology throughout reports and dashboards.
Use headline-style titles when they help communicate key findings.
Example: Using Plain Language to Improve Understanding
Example: Using Plain Language to Improve Understanding
The example below demonstrates how plain language and descriptive titles can make visualizations easier to interpret. Replacing jargon, acronyms, and vague labels with audience-friendly language helps users understand both what the data represents and why it matters.
Before: Less Accessible
Accessibility Challenges
Acronyms and abbreviations assume institutional knowledge.
Technical terminology may be unfamiliar to some users.
Generic titles provide limited context.
Users must decode terminology before interpreting the data.
The chart communicates data but not its significance.
After: More Accessible
Accessibility Improvements
Plain language improves comprehension and reduces ambiguity.
Acronyms and abbreviations have been replaced with descriptive labels.
Headline-style titles communicate key insights upfront.
Users can understand the chart's purpose and key takeaway more quickly.
Audience-friendly terminology reduces interpretation effort.
Quick Test: Would someone outside your department or organization understand the chart's title, labels, and key message without additional explanation?
Resources: Plain Language
Resources: Plain Language
These tools and resources can help you use audience-centered language, meaningful titles, and clear terminology that improve understanding and reduce the need for specialized knowledge.
Plain Language Guidance
Digital.gov Plain Language Guide Series: Federal guidance for writing clear, concise, and user-friendly content.
Center for Plain Language: Practical resources and examples for reducing jargon and improving communication clarity.
Data Visualization Guidance
Harvard: Data Visualizations, Charts, and Graphs: Guidance on communicating information clearly through chart titles, labels, and supporting text.
Highcharts: 10 Guidelines for Data Visualization Accessibility: Includes recommendations for clear labeling, interpretation, and audience-friendly communication.
Storytelling & Communication
Pope Tech: How to Make Charts and Graphs More Accessible: Discusses ways to improve chart comprehension through clearer labeling and communication practices.
A11Y Collective: Includes practical guidance for chart titles, descriptions, labels, and communicating key insights effectively.
Consistency & Cognitive Load
Consistency & Cognitive Load
Why It Matters
Why It Matters
Users should not have to relearn how a report, dashboard, or visualization works as they move between pages. Consistent design patterns reduce cognitive effort and help users focus on understanding the data rather than navigating different layouts, colors, labels, and visual styles.
What to Avoid
What to Avoid
Changing colors, layouts, or terminology between pages.
Placing filters or navigation elements in different locations.
Using different names for the same metric.
Inconsistent chart styles within the same report.
Multiple visual formats for similar information.
Unexpected interactions or navigation behaviors.
What Good Looks Like
What Good Looks Like
Similar functions behave similarly throughout the report.
Colors are used consistently.
Metrics use the same terminology across pages.
Layout and navigation patterns remain predictable.
Charts that present similar information use similar designs.
Users can focus on the data rather than learning the interface.
Example: Creating Consistent Report Designs
Example: Creating Consistent Report Designs
The example below demonstrates how consistent layouts, terminology, colors, and visual styles can reduce cognitive effort and make reports easier to navigate and understand. When users encounter familiar patterns, they can focus on interpreting information rather than relearning how each page works.
Before: Less Accessible
Accessibility Challenges
Similar information is presented using different layouts and visual styles.
Terminology changes between report pages.
Visual elements compete for attention and create inconsistency.
Users must repeatedly learn new design patterns.
Additional cognitive effort is required to locate and interpret information.
After: More Accessible
Accessibility Improvements
Users can focus on insights rather than interface differences.
Consistent layouts make information easier to locate.
Stable terminology reduces confusion.
Visual styles communicate information consistently across pages.
Predictable templates improve navigation and usability.
Quick Test: If users move from one page, chart, or report to another, do colors, terminology, layouts, and visual styles remain consistent?
Resources: Consistency & Cognitive Load
Resources: Consistency & Cognitive Load
These tools and resources can help you create consistent visualizations, reports, and dashboards that reduce cognitive effort and make information easier to interpret.
General Guidance
Highcharts: 10 Guidelines for Data Visualization Accessibility: Practical recommendations for creating clear, predictable, and consistent data visualizations.
Oregon Health Authority: Accessible Data Visualizations Quick Guide: Comprehensive guidance covering organization, readability, navigation, and consistency considerations.
Information Design & Usability
U.S. Web Design System: Data Visualizations: Examples and guidance for creating visualizations that follow predictable, user-centered design patterns
Pope Tech: How to Make Charts and Graphs More Accessible: Discusses strategies for improving comprehension through thoughtful design and presentation choices.
Reducing Cognitive Load
A11Y Collective: Includes recommendations for consistency, clarity, and reducing barriers to interpretation
Data Europa: Data Visualization Guide: Cognitive Load: Explains how visual complexity, inconsistent design choices, and excessive information can increase cognitive effort, and offers strategies for creating visualizations that are easier for users to process and understand.
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