Environmental Data Analysis and Visualization

Communicating Visually

Warm-up exercise

Go to Canvas and have a look at the “Coffee With Co-Workers” study


Read the abstract, skim-read the article, and jot down the following:

  • justification for the study

  • study population, methods, materials

  • the main findings

Dataset of the Day

FEMA National Risk Index

https://hazards.fema.gov/nri/

The audience matters

When we are communicating about research, we have to tailor how and what we communicate depending on who we are communicating with.

  • How much time do they have?

  • How familiar with the subject?

  • How important are the details?

Communicating about research

Rhoda Baer/NIH, Public Domain

Communicating about research

thispersondoesnotexist.com

Communicating about research

dol.gov/agencies/osec

Effectively communicating with visuals

  • What’s the headline?

  • Drawing the eye

  • Conveying the mood

What’s the headline?

What are the most pressing points you want to make with your graph?

statista.com

What’s the headline?

Krzywinski, Martin, and Alberto Cairo. 2013. “Storytelling.” Nature Methods 10 (8): 687–687. https://doi.org/10.1038/nmeth.2571.

What’s the headline?

Krzywinski, Martin, and Alberto Cairo. 2013. “Storytelling.” Nature Methods 10 (8): 687–687. https://doi.org/10.1038/nmeth.2571

What’s the headline?

Krzywinski, Martin, and Alberto Cairo. 2013. “Storytelling.” Nature Methods 10 (8): 687–687. https://doi.org/10.1038/nmeth.2571

What’s the headline?

Krzywinski, Martin, and Alberto Cairo. 2013. “Storytelling.” Nature Methods 10 (8): 687–687. https://doi.org/10.1038/nmeth.2571

Catching the eye

It’s easy for the headline to get lost in a data graph. It’s OK to help the audience find it.

https://www.rashdesign.com/blog/2021/9/24/stevewexler

Exercise: Made you look

For this exercise, I’ll ask you to avert your eyes prior to the slide being shown.

When the slide is shown, pay attention to where on the image your eyes are drawn first, then second, then third, and so on. They may return to the same place more than once.

What do you see?

https://fineartamerica.com

What do you see?

NY Times

What do you see?

https://itravel81.wordpress.com

Drawing the eye to the headline

Knaflic, Cole Nussbaumer. 2019. Storytelling with Data. New York: Wiley.

Drawing the eye to the headline

Knaflic, Cole Nussbaumer. 2019. Storytelling with Data. New York: Wiley.

Conveying the mood

buffalo.edu

Conveying the mood

Lisa Collier/Leeds College of Art

Data storytelling

juicyenglish.com

Data storytelling

Example 1

Example 2

Divide and conquer

  • The Setup Draw in the audience, set the scene

  • The Rise Build the evidence, make the case

  • The Apex The major finding

  • The Resolution Call to action, next steps

Maps as storytelling devices

Example 1

Example 2

Example 3

Spatial data

Spatial data is data related to a location

Spatial data

Spatial data is data related to a location

Location

  • X position (longitude, easting, etc.)

  • Y position (latitude, northing, etc.)

  • Z position (elevation [optional])

Attributes (literally anything else)

  • Name

  • ID number

  • Species

  • Weight

  • Color

  • Condition

  • Recording method

Spatial data models

Vector

Raster

The sf package

The simple features or sf package gives R functions for handling vector data and interfacing it with the tidyverse.

library(tidyverse)
library(sf)

The sf package

vernalPools<-st_read("data/GISDATA_CVP_PTPOINT.shp",quiet=TRUE)

vernalPools<-st_zm(vernalPools,drop = TRUE, what = "ZM")

vernalPools
Simple feature collection with 7881 features and 3 fields
Geometry type: POINT
Dimension:     XY
Bounding box:  xmin: 34452.43 ymin: 781370.8 xmax: 329087.3 ymax: 958316.4
Projected CRS: NAD83 / Massachusetts Mainland
First 10 features:
   cvp_num                       criteria  certified                  geometry
1     5098 Obligate Species, Fairy Shrimp 2009-05-31 POINT (101876.8 878024.9)
2     4385               Obligate Species 2007-01-08 POINT (124514.6 895968.7)
3     7707               Obligate Species 2016-12-29 POINT (253914.4 830115.9)
4     7627               Obligate Species 2015-08-06 POINT (119130.7 877295.4)
5     1826               Obligate Species 1999-07-15 POINT (188430.5 937917.1)
6     4622               Obligate Species 2007-10-17   POINT (213979.5 863452)
7     6711               Obligate Species 2012-06-11 POINT (271080.4 935932.4)
8     1306               Obligate Species 1997-09-18   POINT (103664 872042.3)
9     6997               Obligate Species 2013-02-27 POINT (238222.5 927072.7)
10    3441               Obligate Species 2004-06-17 POINT (199376.9 865967.6)

The sf package

ggplot() + 
  geom_sf(data = vernalPools,aes(color=year(certified)),size=0.5) +
  theme_minimal()

This week

Working with vector data in R

Making data spatial

Making maps with ggplot2

Communicating about research

How will you tell Milo about coffee with co-workers?