21 Peer Review Visualizations

TODAY’S GOALS

Practice giving and getting feedback on your visuals

Refine your data story through the feedback process

For more on this topic

Read:

Communicating with Data (Nolan and Stoudt)

WHERE ARE WE?!? Data Storytelling

Data Storytelling is the process of creating a narrative around a dataset. This narrative can be used to inform, persuade, or entertain. It is a way to communicate the insights we’ve gained from our data to others.

21.1 Warm-up

Effective communication = effective visuals + clear narrative

21.1.1 Effective visuals

Let’s review from the beginning of semester.

Professionalism

meaningful axis labels

figure caption

Accessibility

alternative text

color blind friendly colors

Design details

consider glyph choice

consider color choices

facilitate comparison

use contrasts to draw attention

Ethics

Don’t mislead

Consider visibility, privacy, power, emotion & embodiment, pluralism, context

Let’s consider a few other visuals. What is effective? What could be improved?

21.1.2 Clear narrative

When preparing to present a visualization, consider the following:

Motivation & Context
- What is the question you are answering, and why is it important?
- What data context does the audience need to understand the visual? (W’s?)
Orientation
- What aspects of the visual should you explain to provide necessary orientation?
- Walk through guides (axes, color legend, etc.)
Highlights
- Hone in on one or two interesting data points and tell the story behind them.
- Explain how the visual aspects of the viz reflect that story (this reinforces how they should interpret the viz).
Big Picture
- What are the overall trends or takeaways?
- What are the implications for them? Why does it matter?
- What comparison are you wanting to highlight?

21.1.3 Presenting Visualizations

Speak slowly
- It takes people some time to wrap their heads around a new viz.
Practice ahead of time with a friend. Practice by yourself. Refine the viz if necessary!

21.2 Exercises

In small groups of 3-4 people, complete the following two exercises for each person.

21.2.1 Exercise 1

Present your visualization (2 minutes) making sure you cover

Motivation & Context
Orientation
Highlights
Big Picture

21.2.2 Exercise 2

Discuss as a group ways of improving the visualization to make it more effective (8 minutes)

Comment on the effective features of the graphic
Offer concrete suggestions to improve the visualization
- different glyphs
- different colors
- different layout
- consider faceting, position
Ask questions about the data that the visual prompts
Brainstorm with to come up with ideas and questions that have not yet been explored or visualized

Once your group is done, use this time to update your graphic based on that feedback.

# Peer Review Visualizations ```{r setup, echo = FALSE, warning = FALSE} knitr::opts_chunk$set(collapse = TRUE, warning = FALSE, message = FALSE, fig.height = 2.75, fig.width = 4.25, fig.env='figure', fig.pos = 'h', fig.align = 'center') ``` ```{r, echo=FALSE, results="hide", warning=FALSE, message=FALSE} # Load packages library(tidyverse) library(tint) library(mosaic) question_num <- 0 NextQ <- function() { question_num <<- question_num + 1 return (question_num) } library(conflicted) conflict_prefer("rename", winner = "dplyr") conflict_prefer("filter", winner = "dplyr") conflict_prefer("smiths", winner = "tidyr") conflict_prefer("melt", winner = "reshape2") conflict_prefer("count", winner = "dplyr") conflict_prefer("group_by", winner = "dplyr") conflicts_prefer(ggthemes::theme_map) conflicts_prefer(base::sum) conflicts_prefer(base::min) conflicts_prefer(base::max) conflicts_prefer(base::mean) ``` <div class='content-hidden'> **SETTLING IN** Sit with people that **are not** in your project group. Introduce yourself. Share what's at the top of mind today. \ \ \ \ \ \ \ \ </div> > **TODAY'S GOALS** > > - Practice giving and getting feedback on your visuals > - Refine your data story through the feedback process \ \ \ \ > **For more on this topic** > > Read: > > - [Communicating with Data](https://global.oup.com/academic/product/communicating-with-data-9780198862758?cc=us&lang=en&) (Nolan and Stoudt) \ \ \ \ **WHERE ARE WE?!? Data Storytelling** - **Data Storytelling** is the process of creating a narrative around a dataset. This narrative can be used to inform, persuade, or entertain. It is a way to communicate the insights we've gained from our data to others. \ \ \ \ ## Warm-up Effective communication = effective visuals + clear narrative ### Effective visuals Let's review from the [beginning of semester](07-effective-viz.html). > - Professionalism > - meaningful axis labels > - figure caption > - Accessibility > - alternative text > - color blind friendly colors > - Design details > - consider glyph choice > - consider color choices > - facilitate comparison > - use contrasts to draw attention > - Ethics > - Don't mislead > - Consider visibility, privacy, power, emotion & embodiment, pluralism, context Let's consider a [few other visuals](https://viz.wtf/). What is effective? What could be improved? ### Clear narrative When preparing to present a visualization, consider the following: - Motivation & Context - What is the question you are answering, and why is it important? - What data context does the audience need to understand the visual? (W's?) - Orientation - What aspects of the visual should you explain to provide necessary orientation? - Walk through guides (axes, color legend, etc.) - Highlights - Hone in on one or two interesting data points and tell the story behind them. - Explain how the visual aspects of the viz reflect that story (this reinforces how they should interpret the viz). - Big Picture - What are the overall trends or takeaways? - What are the implications for them? Why does it matter? - What comparison are you wanting to highlight? ### Presenting Visualizations - Speak slowly - It takes people some time to wrap their heads around a new viz. - Practice ahead of time with a friend. Practice by yourself. Refine the viz if necessary! \ \ \ \ ## Exercises In small groups of 3-4 people, complete the following two exercises for each person. ### Exercise 1 Present your visualization (2 minutes) making sure you cover - Motivation & Context - Orientation - Highlights - Big Picture ### Exercise 2 Discuss as a group ways of improving the visualization to make it more effective (8 minutes) - Comment on the effective features of the graphic - Offer concrete suggestions to improve the visualization - different glyphs - different colors - different layout - consider faceting, position - Ask questions about the data that the visual prompts - Brainstorm with to come up with ideas and questions that have not yet been explored or visualized *Once your group is done, use this time to update your graphic based on that feedback.* \ \ \ \ <div class='content-hidden'> ## Wrap-up - Upcoming due dates </div>