Recurring Accessibility Failures in Data Storytelling — and How to Fix Them

Many data visualization guidelines promote best practices such as direct labeling or progressive disclosure. However, institutional accessibility audits and dashboard reviews consistently reveal a deeper problem: charts may meet technical WCAG criteria yet still create barriers for screen reader users, keyboard users, and people with cognitive disabilities.

This poster synthesizes recurring failure patterns observed across higher education accessibility reviews of dashboards, learning analytics platforms, and reporting environments. Rather than presenting a general checklist, it identifies six high-impact breakdown points where accessibility most frequently fails in real-world data storytelling — and demonstrates targeted corrections aligned with WCAG 2.x success criteria.

Each breakdown category includes:

• The specific accessibility barrier
• The primary user groups impacted (screen reader, keyboard, low vision, cognitive)
• A before-and-after visual example
• The relevant WCAG criteria
• A concise, production-ready remediation technique

The six breakdowns are organized by the type of exclusion they produce:

1. Legend Dependence → Non-Perceivable Category Encoding
2. Insight Omission → Interpretive Inequity
3. Hidden Interaction Controls → Keyboard Trap Risk
4. Scale Manipulation → Misleading Comparative Interpretation
5. Overloaded Multi-Variable Charts → Cognitive Overwhelm
6. Filter-Dependent Meaning → Context Loss for Assistive Technology Users

The focus is not aesthetic refinement, but restoration of functional and interpretive access. Attendees will leave with a compact, practice-informed remediation lens that can be applied immediately in accessibility audits, QA workflows, and production dashboard environments.