User Guide
Blog
Reference
Examples
Download
Github

Accessibility in chart design it’s about creating an environment where all users have equal access to information. Visual impairments, color vision deficiencies, and cognitive disabilities can all impact how a person interacts with a chart. When we fail to take these into account, we sideline those individuals from the discourse that data can ignite.

 

Embracing the Principles of Accessible Design with Clip

Permeability means that the information presented in charts must be available to all users in some form they can perceive. When working with Clip to develop charts, providing alternatives for non-text content is important. Incorporating alt text for graphical components allows screen readers to convey the chart’s purpose and data to users who cannot see them.

Operability revolves around the idea that users must be able to navigate and use the interface to interpret chart data. This aspect is particularly necessary for those relying on keyboard navigation. It is important to facilitate keyboard shortcuts and tab-indexes that help users move through the elements of a chart. Controls should be intuitive, and chart information must be accessible without relying on a mouse or touch screen.

Charts must convey information clearly and straightforwardly. This includes logical structure and predictable actions within the Clip platform. When building charts, it is recommended to emphasize simplicity and coherence in the presentation of data. This clarity helps users with cognitive limitations to comprehend the information being presented.

Language and labeling within charts should also be intuitive and free from unnecessary jargon. If technical terms are required, a glossary or explanation within the chart can provide additional support for individuals unfamiliar with the terminology.

The tool should generate charts that maintain their accessibility features across different platforms and devices. This also means adhering to established accessibility standards, such as the Web Content Accessibility Guidelines (WCAG), ensuring that charts can be interpreted by a variety of assistive technologies.

Creators should regularly consult users with disabilities for direct feedback and continuously test their charts for accessibility throughout the development process. This champions an environment where the importance of access to information is celebrated and diligently pursued.

 

Chart Structures and Types

The bar chart is one of the most accessible chart types because it relies on straightforward visual elements – rectangular bars. Bar charts are conducive to screen readers and alternative text descriptions due to their simple structure. Each bar’s length or height can correlate directly with a data value, which can be easily articulated in text form. In Clip, using a bar chart allows users to comprehend data comparisons across categories with ease, making them a preferred choice for accessible design.

Line graphs are a dynamic tool for displaying trends over time. They consist of a series of points connected by lines, showing how values rise and fall. It’s important to distinguish between multiple lines clearly. Clip can facilitate this by incorporating markers or varied line styles, ensuring that each line is perceivable for users with visual impairments or color blindness. The implementation of clear, descriptive legends and proper alternative text can make line graphs accessible by narrating the trends and changes they depict.

Pie charts present unique challenges for accessibility due to their reliance on color to differentiate between slices of the pie. To address this in Clip, it is advisable to include clear labels and patterns or textures for each segment. This improvement assists those with color vision deficiencies to distinguish between sections. An additional method to make pie charts more accessible is to supplement them with a textual representation of the data, ensuring that the information conveyed by the chart is not missed.

Some data sets require more complex forms of visualization, such as scatter plots or radar charts, to convey relationships or multiple variables. These complex charts can often be challenging to interpret, particularly for those with visual or cognitive disabilities. 

When employing complex charts, it is critical to offer comprehensive explanations that guide the user through the chart’s intentions, layout, and conclusions. Tools and features within Clip should be utilized to annotate these charts elaborately, ensuring that every user, regardless of ability, can access the information presented.

 

Selecting Colors and Textures Wisely

High contrast in color schemes significantly impacts the readability of charts. One must prioritize color choices that stand out distinctly from one another as well as from the background. This approach ensures that individuals with color vision deficiencies or low vision can perceive the information. A common recommendation is to use dark-colored text and elements on light backgrounds or vice versa.

Accessible Chart Clip
To create universally accessible charts, incorporate color palettes in Clip that avoid common problematic color combinations, like reds and greens, which are often indistinguishable to those with color blindness. Tools like color blindness simulators can help creators view their charts through the lens of various color vision deficiencies, guiding them to make informed decisions about color use.

When a chart’s readability cannot solely depend on color, introducing patterns such as stripes, dots, or crosshatching can mark distinct areas or lines. The clip should offer a variety of easily distinguishable textures that can be applied to elements within the chart to ensure no user is disadvantaged.

It is important to maintain a clear distinction in texture when overlaying patterns to prevent visual confusion. Simple and easily recognizable textures can alleviate potential comprehension issues, aiding users in distinguishing data points without needing to rely on color differentiation.

Consistency in color and texture application across different charts is vital for a user’s cognitive understanding. Employing the same color or pattern to represent a specific data series or category throughout your visualization aids in the user’s retention of information.

The legends must be visually distinct and accompanied by descriptive text that can be read by screen readers, further enhancing the accessibility of the chart.

 

Incorporating Alt Text and Long Descriptions

Alt text, short for “alternative text,” is a concise description that functions as a textual substitute for images, including charts and graphs. When images cannot be rendered, or when users are reliant on screen readers, alt text ensures that the content is not lost. Alt text should succinctly communicate the critical information the chart represents, highlighting the main findings and trends conveyed by the visualization.

When crafting alt text for charts:

Convey important information about the chart briefly and compactly.

Clearly state the most significant data points and what they signify to the reader.

Ensure the alt text aligns with the surrounding content and explains the chart’s relevance.

Long descriptions offer the space to elaborate on complex charts, providing a more detailed narrative of the data and its implications. Long descriptions enable users to grasp the intricacies of the visualization that might include multiple data sets, trends, and relationships that alt text alone cannot adequately represent.

For long descriptions:

Explain the type of chart used and why it was chosen for the data presented.

List detailed information that may include scales, axis labels, data series names, and important data points.

Summarize what the chart illustrates about the dataset as a whole, including any trends, correlations, or anomalies.

It is imperative for a tool like Clip to integrate functionality for adding both alt text and long descriptions with ease. This ensures that the creators of the charts are provided with the means to make their visualizations fully accessible. Since alt text is typically limited in length, Clip should offer the option of linking to or embedding a longer description that can be accessed by users if they require more information.

 

Ensuring Keyboard Navigation and Screen Reader Compatibility

Keyboard navigation enables users to interact with a chart using keyboard keys, such as the Tab, Enter, and Arrow keys, which stand as gateways to a chart’s interactive elements. It is important to ensure a logical tab order. Users should be able to move through the chart’s elements in a sequence that mirrors the flow of information.

For effective keyboard navigation:

Ensure that the tab order corresponds with the logical flow of the chart, usually left to right and top to bottom.

Display visible cues to indicate the current focal element selected through keyboard navigation, which might take the form of a highlighted outline or a color change.

Make sure that all interactive parts of the chart, such as toggles for data series or filter controls, are reachable and operable via keyboard.

Screen readers convert text and image content into speech or braille output, aiding those who cannot view content on the screen. It about translating visual information into descriptive auditory information.

Guiding aspects for screen reader compatibility:

Apply ARIA roles and properties to inform screen reader users of the chart’s structure and interactive features.

All visual elements, including charts and images, should have textual equivalents like alt text and long descriptions that screen readers can process.

Offering a data table view of the chart’s information can be an alternative form for screen readers to access data in a non-visual format.

For users who rely on both keyboard navigation and screen readers, Clip must seamlessly combine these two interactive features. As a user tabs through a chart, the screen reader should announce the data or element focused, such as axis labels, data points, and interactive controls.

Creators need to test their charts with various screen readers and input methods to ensure compatibility and ease of use. The end goal is fully accessible charts where all elements are navigable and audibly descriptive, providing a comparable experience to viewing the chart visually.

 

Including an Accessible Data Table

An accessible data table is structured so that it can be read linearly by screen readers, allowing all users to interpret the data comprehensively. Strict adherence to accessibility principles ensures that every user can navigate the data with ease.

Aspects to consider include:

Use correct HTML tags such as <table>, <th>, <tr>, and <td> to define the table, header cells, rows, and data cells, respectively. Proper markup facilitates screen readers in deciphering the table’s structure.

Designate header cells for rows and columns using <th> tags and the scope attribute to clarify the relationships between elements of the table.

Provide captions with the <caption> tag to give an overview of the table’s content, and summaries when necessary, to describe the table configuration and how to navigate it.

Include features such as sortable columns and filters that are also operable through keyboard interaction, ensuring that all functionalities are accessible to users without a mouse.

Having the capability to automatically generate an associated accessible data table from a chart is a significant advantage. It allows creators to ensure consistency and accuracy of data across both visual and text-based presentations.

Enable the tool to create data tables from chart data directly, ensuring that the visual data and the data tables are always in sync.

Provide options to customize the data table for various needs, such as choosing which data points to include or how to group information.

Users with limited internet bandwidth or those using text-only browsers also benefit from having the option to access data in a non-graphical format. Accessible data tables serve as a failsafe against technological constraints that might render visual charts incomplete or inoperative.

 

Other posts

  • Clip for Financial Data
  • 5 Questions to Ask Your Data Annotation Provider
  • Choosing the Right Chart Type for Your Data
  • Combining Clip Charts with D3.js
  • Enhancing User Experience with Thoughtful Clip Chart Design 
  • Clip in Data Journalism
  • Scripting Multi-page Reports with Clip
  • Improve Your Cybersecurity Skills with Online Courses
  • Clip in the Classroom - Teaching Data Visualization Basics
  • Building a Gallery of Clip Charts for Your Website