Chartability: How Accessible Is My Chart?

A unified methodology to serve the intersection of data visualization and accessibility.

The need for easily accessible data experiences has been long overlooked. Despite the fact that the Web Content Accessibility Guidelines (WCAG) by the Web Accessibility Initiative (WAI) have been in place for the past 22 years, inclusive design principles pertinent to the fields of data communication, data science, data analysis, and visualization have not undergone any significant changes. The majority of access challenges that affect data visualization (such as cognitive/neurological, vestibular, and motor concerns) have remained unaddressed. Because of this, accessibility is still a secondary factor in data visualization, and the ad hoc, focused solutions that have been suggested previously have not resulted in major advancements.

While general accessibility guidelines are helpful, determining whether complex data systems are inaccessible can be a challenging and frequently expensive undertaking. However, Frank Elavsky begins to address the gap in accessibility evaluations with his own set of heuristics called Chartability. With a total of 50 heuristics, Chartability serves to provide a framework to examine the accessibility of data experiences, interfaces, and systems to produce more inclusive environments for users with disabilities. It is aimed at researchers, analysts, designers, developers, editors, and accessibility specialists.

To date, Tableau, Microsoft Excel and PowerBI, JavaScript (D3, Vega-Lite, Highcharts, Visa Chart Components), Python (Altair, Bokeh, and matplotlib), R (ggplot2), design drawings and low to medium-fidelity artifacts (Illustrator, Figma, Sketch) have all been evaluated using Chartability. This has led to a community researched Version 2 of the heuristics that include more tests and resources.

What is Chartability?

Chartability is a set of testable questions for evaluating information-rich interfaces, especially those that have data visualizations. Elavsky breaks down his heuristics under 7 main principles categorized as Perceivable, Operable, Understandable, and Robust (POUR) and the last three as extensions of Robust with Compromising, Assistive, and Flexible (CAF).

• Perceivable : Users must be able to easily identify content using their senses: sight, sound, and touch.
• Operable: All controls must be error-tolerant, discoverable, and multi-modal (not just mouse operable, but using keyboard, etc).
• Understandable : Any information or data are presented without ambiguity, with clarity, and in a way that minimizes cognitive load.
• Robust : The design is compliant with existing standards and works with the user’s compliant, assistive technologies of choice.
• Compromising (Understandable, yet Robust): Information flows must provide transparency, tolerance, and consideration for different ways that users with assistive technologies and disabilities will prefer to consume different information.
• Assistive (Understandable and Perceivable but labor-reducing): Interface must be intelligent and multi-sensory in a way that reduces the cognitive and functional labor required for use.
• Flexible (Perceivable and Operable, yet Robust): Design must respect user settings from user agents (browsers, operating systems, applications) and provide presentation and operation control.

View the entire set of heuristics here.

Getting started with Chartability

It can be challenging for beginners to start an accessibility evaluation when there are 50 standards to review. So, in order to help novices adjust to it more confidently and efficiently — Chartability marks 14 standards (initially 10) as critical. These 14 critical standards were refined based on user feedback from field specialists who utilized the heuristics to evaluate their work.

Chartability’s initial 10 Critical Heuristics.

Chartability is designed to support both rapid pass and deep dive audit approaches. To new users, auditing may need between 2 and 8 hours to perform a full pass of Chartability, whereas a highly skilled auditor might be able to casually review an artifact in as little as 30 minutes or even have heuristics in mind while they are examining their own creative work.

Why is this needed? And how can we take this forward?

Designing for accessibility needs to go beyond compliance. We need to begin focusing our efforts on creating good experiences for true inclusion. As technology develops at an exponential rate, it is critical to establish fundamental standards that can be used to make new visualization advancements — like sonification and dynamic tactile graphics — accessible to the whole user population from ground zero. But if we overlook this, we widen the social and technological gap that people with disabilities already endure. As ethical designers and data practitioners, adopting tools like Chartability and adding to the research in this space adds to significant changes that ensure data visualizations never serve to exclude.

Reference

• Elavsky, F., Bennett, C., & Moritz, D. (2022). How accessible is my visualization? Evaluating visualization accessibility with Chartability. Computer Graphics Forum, 41(3):57–70, 2022.