# Data Visualization for Public Policy

![bg fit right](mosaic.jpg)

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## Recap: Why Do We Create Visualizations?

- To **better understand** large, complex datasets.
- To **influence others** through compelling, evidence-based storytelling.

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## Influence: The Power of Visual Communication

Effective data visualizations can:

- Draw attention to critical problems or potential solutions.
- Argue for specific policy interventions.
- Connect an audience with large and potentially abstract data concepts.

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## Key Ideas Exercise

What are *your* golden rules of data visualization?

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## (Some) Key Rules for Effective Data Visualization

### 1. Audience-Centered Design

- Take time to consider and understand your audience's background, expertise, and information needs.
- The "best" data visualization is one that the audience understands & remembers.

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### 2. **Prioritize Truthful Representation**

- Correct chart types & encodings.
- Never sacrifice **data integrity** in the name of a "better" chart.
- Avoid misleading choices: truncated axes, dual axes, etc.
- Consider the role of **uncertainity** in representing your data.

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<!-- Mackinlay's Effectiveness Hierarchy-->

![bg fit](../01.gog-altair/effectiveness.png)

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### 3. **Maximize Clarity and Comprehension**

- Simplify complex information where possible. It is OK to refer a user to a table or other source for deeper analysis.
- Remove unnecessary visual elements --  "chart junk"
- Guide the viewer's attention to key insights with **labeling**.

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## Tufte's Key Ideas Revisited

![bg fit right](../03.charts/tufte.png)

- Graphical Integrity: Above all else, show the data.
- Maximize the data-ink ratio.
- Minimize chart junk.
- Aim for high chart density, consider *small multiples*.
- Revision & Editing are essential.

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### 4. **Optimize for Accessibility**

- Use color-blind friendly palettes.
- Ensure readability for viewers with different visual capabilities. (Contrast,font size, etc.)
- Provide *alternative text descriptions* in web presentations.
    - `<img src="..." alt="A graphic representing the length of rivers..." />`
- Accessibility tools: contrast/color/WCAG checkers.

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### 5. **Build a Compelling Narrative**

- Create a clear, coherent story and use graphics to support it.
- Each chart should have a clear "why" -- don't make users wonder why you're showing them something.
- Use visual elements & conventions to guide the viewer through key arguments and order.
- Connect data to broader context and implications.

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### 6. **Embrace Iterative Improvement**

- Seek feedback from diverse perspectives, especially those represented in your audience.
- Be willing to revise and refine, if someone had an issue others will too.

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### 7. **Consider Ethical Implications**

- Represent marginalized groups respectfully: color choices, language.
- Remember that pixels often represent people, dismissing outliers/etc. should not be done without consideration.
- Be transparent about data sources and limitations.
- Use visualization as a tool for **understanding and persuasion, not manipulation**.

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## Conclusion

Effective data visualization is both an art and a science.

Understand your data and what you people to understand.

Center your audience.

Prioritize clarity & truth.

Be creative & have fun!