Data Visualization SpecialistAccessibility and Standards2 promptsIntermediate → Advanced2 single promptsFree to use

Accessibility and Standards AI Prompts

2 Data Visualization Specialist prompts in Accessibility and Standards. Copy ready-to-use templates and run them in your AI workflow. Covers intermediate → advanced levels and 2 single prompts.

AI prompts in Accessibility and Standards

2 prompts
IntermediateSingle prompt
01

Accessibility Audit for Data Viz

Audit this visualization for accessibility and recommend improvements. Visualization: {{visualization_description}} Deployment context: {{context}} (web, print, presentation, em...

Prompt text
Audit this visualization for accessibility and recommend improvements. Visualization: {{visualization_description}} Deployment context: {{context}} (web, print, presentation, embedded application) Target WCAG level: {{wcag_level}} (AA is the standard; AAA for government/public sector) 1. Color accessibility: - Color contrast: check foreground vs background for all text and key visual elements - Normal text: minimum 4.5:1 contrast ratio (WCAG AA) - Large text (18pt+ or 14pt bold): minimum 3:1 - Visual elements (charts, icons): minimum 3:1 against adjacent colors - Color independence: can the chart be understood by someone who cannot see color? - Add: patterns, shapes, textures, or direct labels as alternatives to color-only encoding - Colorblind simulation: run the chart through a deuteranopia / protanopia simulator 2. Text accessibility: - Minimum font size: 12pt for body text, 10pt minimum for chart labels - Font choice: avoid decorative or condensed fonts for data labels - Text alternatives: all charts need alt text describing the key finding (not just 'a bar chart') - Alt text format: 'Bar chart showing [metric] by [dimension]. [Key insight in one sentence]. [Data source and date range].' 3. Chart-specific accessibility: - Tables as alternatives: complex visualizations should have a data table option for screen readers - Keyboard navigation: interactive charts must be navigable by keyboard (Tab, Enter, Arrow keys) - Focus indicators: visible focus highlight for all interactive elements - ARIA labels: for web-based charts, add aria-label attributes to chart containers 4. Motion and animation: - Respect 'prefers-reduced-motion' media query — animations should be disableable - No flashing content at > 3Hz (seizure risk) - Provide static alternative for all animated charts 5. Cognitive accessibility: - Consistent layout: same chart types in the same position across pages/dashboards - Clear headings: descriptive titles and section headings - Plain language: chart titles use plain language, not industry jargon - Consistent color coding: same color always means the same thing - Avoid information overload: maximum 5–7 items requiring comparison per chart 6. Testing tools: - WebAIM Contrast Checker for color contrast - Deque's aXe browser extension for WCAG compliance - Screen reader testing: NVDA (Windows), VoiceOver (Mac/iOS) - Colorblind simulators: Coblis, Sim Daltonism Return: accessibility audit table (issue, WCAG criterion, severity, fix), specific fixes for the visualization described, and alt text for the chart.
AdvancedSingle prompt
02

Style Guide for Data Visualization

Create a data visualization style guide for this organization. Organization: {{organization}} Brand colors: {{brand_colors}} Primary tools: {{tools}} Typography system: {{typogr...

Prompt text
Create a data visualization style guide for this organization. Organization: {{organization}} Brand colors: {{brand_colors}} Primary tools: {{tools}} Typography system: {{typography}} Audience for the style guide: {{audience}} (data analysts, developers, designers) A style guide ensures all visualizations across the organization look coherent, communicate clearly, and meet accessibility standards. 1. Color system: PRIMARY PALETTE (for data encoding): - Primary: {{primary_color}} — use for the most important series or highlight - Secondary: 3–5 supporting colors for categorical series - Neutral: grey scale for non-data elements (axes, gridlines, background text) - Alert: one red/orange for negative values or warnings SEQUENTIAL PALETTES: - Single-hue: light-to-dark of the primary color - Multi-hue: define the start and end color (perceptually uniform progression) DIVERGING PALETTES: - Define: negative color, neutral midpoint color, positive color RULES: - Maximum 8 colors in any single chart - Never use color as the only encoding (add labels, patterns, or shapes) - All palettes must pass colorblind-safe test 2. Typography: - Chart title: {{heading_font}}, {{title_size}}pt, bold - Axis labels: {{body_font}}, 11pt, regular - Data labels: {{body_font}}, 10pt, regular - Annotations: {{body_font}}, 10pt, italic - Numbers: use tabular figures (all same width) for alignment in tables 3. Chart formatting standards: - Minimum chart width: 480px (for web); 3 inches (for print) - Minimum height: 60% of width for most charts - Background: white (#FFFFFF) or transparent - Gridlines: horizontal only, light grey (#E0E0E0), 0.5pt - No chart borders or shadows - Axis lines: left axis only (y-axis), light grey, 0.5pt - Tick marks: none unless necessary 4. Chart title standards: - Format: insight statement (not a label) - Length: 1 line maximum for presentation; 2 lines for reports - Capitalization: sentence case (not title case) - No period at end of title 5. Number formatting: - Revenue: $1.2M (> $1M), $456K (> $1K), $123 (< $1K) - Percentages: 23.4% (1 decimal), 100% (no decimal) - Counts: comma separator every 3 digits - Dates: 'Jan 2024' for months, 'Q1 2024' for quarters, '2024' for years - Ratios: 2.3× (not 2.3x) 6. Template files: - Provide: Tableau workbook template, Power BI template file, Python rcParams settings Return: complete style guide document with all specifications, hex codes, template settings for each tool, and a one-page quick reference card.

Recommended Accessibility and Standards workflow

1

Accessibility Audit for Data Viz

Start with a focused prompt in Accessibility and Standards so you establish the first reliable signal before doing broader work.

Jump to this prompt
2

Style Guide for Data Visualization

Review the output and identify what needs follow-up, cleanup, explanation, or deeper analysis.

Jump to this prompt

Frequently asked questions

What is accessibility and standards in data visualization specialist work?+

Accessibility and Standards is a practical workflow area inside the Data Visualization Specialist prompt library. It groups prompts that solve closely related tasks instead of leaving users to search through one flat list.

Which prompt should I start with?+

Start with the most general prompt in the list, then move toward the more specific or advanced prompts once you have initial output.

What is the difference between a prompt and a chain?+

A single prompt gives you one instruction and one output. A chain is a multi-step sequence designed to build on earlier results and produce a more complete workflow.

Can I use these prompts outside MLJAR Studio?+

Yes. They work in other AI tools too. MLJAR Studio is still the best fit when you want local execution, visible code, and notebook-based reproducibility.

Where should I go next after this category?+

Good next stops are Chart Design Principles, Dashboard Architecture, Advanced Visualization Types depending on what the current output reveals.

Explore other AI prompt roles