Data visualization

GDES-200 fall 2019 (David Ramos, American University Design)
ramos@american.edu · office hours

photo of Navy Yard

This semester, we’ll look at how the climate crisis will affect D.C., examining scenarios for summertime high temperatures, coastal flooding, and a data source of your own choice.

Dataset 1: High tide flooding

Last week, the Potomac River’s waters washed over the seawall near the Lincoln Memorial and flooded streets in Alexandria, driven by the position of the moon and Tropical Storm Melissa offshore. (Capital Weather Gang has more, with photos.)

In 2018, D.C. saw 22 days of flooding at high tide. These sorts of coastal flooding events will become ever more common as the climate warms. Under the most likely climate scenario, the District will see high tide flooding from 166–294 days/year in 2050. Areas at risk from storm surges and heavy rainfall are even larger—a DC DOEE map of flood risks shows the Potomac and Anacostia riverfronts, plus the National Mall, underwater in the worst-case hurricanes.

You can view a Workbench workflow set up to reformat and plot these data. You can download the source data below, in the data section of this document.

Dataset 2: Hot summer days

The District, like other major cities, has embarked on a process of planning for the climate emergency. The planning documents note that soaring summertime temperatures will mark a particular hazard. Heat waves present threats to the health of D.C. residents, especially seniors, and young children, and people with existing medical conditions. The city averages 11 days over 95°F, but it will see 40–70 days by 2080. You can download the source data below, in the data section of this document.

Dataset 3: Your choice

Add another slice of data that you find relevant. Choose something that expands on the flooding and heat data, putting it in a broader or more personal context. These other pieces could take an array of forms, including:

Examples

See information design examples that combine different types or scales of data.

Design + process

For this project, design a document that presents these risks. Show your data in the form of charts, diagrams, maps, or (visually rewarding) tables.

Process

  1. Read background information—assigned readings on the schedule, and some of the additional material here.
  2. Look at the data that illuminate that story (we’ll be using Workbench in class, though a spreadsheet or statistical program might also suffice), and plot the data so that you understand them. Think about how you’d like to organize your data.
  3. Sketch out your final layout, on paper. Decide on the size and position of text and graphical elements.
  4. Prepare rough visualizations in an analytical tool.
  5. Bring those rough visualizations into Illustrator and improve their readability and visual clarity.
  6. Lay out the final document in InDesign or Illustrator. Print and export to PDF.

We will have desk critiques, small-group critiques, and all-class critiques throughout this process. At every stage, if you can imagine two or three alternatives, try all of them.

Format specifications

Typefaces

You may only use the fonts listed here. If you use two fonts, it would be prudent to pick a serif and a sans serif.

Commercial fonts

These may or may not be available to you through Adobe Fonts. If a font isn’t available, try another font on this list.

Free/open source

Download and install. See Apple documentation on how to install a font on a Mac. You can download a package containing OTF files for all these fonts (ZIP).

photo of river bank with birds

Data

Work with temperature and flooding data for D.C. Start by downloading a ZIP file containing data excerpts.

Summer temperatures

The file temperature.csv contains historical and projected temperature averages for Washington, D.C. They come from a report produced by a consultants who were working for the D.C. Department of Energy and the Environment:

Hayhoe, Katharine, and Stoner, Anne. “Climate Change Projections For the District of Columbia.” 2015.

Table of summer temperatures

These are data contained in temperature.csv.

Time period Summer high Summer night low Hot days Heat index days
1991 to 2010 average 87 66 11 30
2020s 89.5 to 90 68.5 to 69 19 to 21 50
2050s 92 to 94 71 to 74 30 to 45 70 to 80
2080s 93 to 97 72 to 76 40 to 70 75 to 105

About the summer temperature data file

The predicted, future values are a range between high and low scenarios.

Tidal flooding

The file flooding.csv contains high tide flooding data for Washington, D.C. These data are a reformatted extract from a larger data file (CSV), which accompanied a NOAA report:

Sweet, W.V., G. Dusek, J. Obeysekera, and J. Marra. “Patterns and Projections of High Tide Flooding Along the U.S. Coastline Using a Common Impact Threshold. NOAA Tech. Rep. NOS CO-OPS 86.” 2018.

Again, you can work with a Workbench workflow that reformats and plots these data.

About the flooding data file

The values in this table are the number of days when tides were high enough to cause flooding, per year. (In this report, the historical data stop in 2016; 2018 saw some 22 days of tidal flooding.)

Location: NOAA Tide Gauge 8594900, Washington Channel, Washington, D.C. (The tidal range for this location runs about 2.5–3 ft.)

NaN entries indicate that the station was not in service, or that there were insufficient data.

The named scenarios (“low,” “int_low,” etc.) are the global sea level rise scenarios the U.S. Federal Interagency Sea Level Rise and Coastal Flood Hazard Task Force. Short but oversimplified answer: the intermediate (“int”) or intermediate-high (“int_high”) scenarios are most likely.

Map assets

In case you’d like to work with maps. Presented here in PDF or SVG format. You can edit these files, which are vector graphics, in Illustrator.

You can find additional maps to edit—look for SVG formatted graphics, freely licensed—Wikimedia Commons is a good starting point.

photo of fuel dock

More information

Sea level rise and climate

Washington, D.C.

The Anacostia River

CSOs and water quality