In chapter 3 of Data Feminism, they talk a lot about the history of scholarship on best practices for data visualization and how some of them may inadvertently perform the “god trick” in presenting itself as all-knowing, totalizing, and neutral standpoints on a given set of data. That is, the “view from nowhere” that suggests all can be seen by viewing these specific lines, bars, etc.
Their argument is that, if you are not offering up inaccurate data that would be lying or offering an invalid interpretation (as is done with misleading graphs we saw in the video on the previous page), then why not embrace emotion and embodiment that capture attention and interest?
Things like:
- Using color
- Using images
- Using motion
- Adjusting font type or size
- Tone and rhetoric of language used
- Using interaction
- Playing with size (again, if not misleading)
- Performance or audio
D’Ignazio and Klein call this “data visceralization” when writers use elements like the above to try to get people emotionally invested in the visualization while still offering valid and accurate interpretations of data. As they argue with the New York Times’ “gauge” for elections, such work also can help communicate non-intuitive information.
Don’t limit yourselves with being creative in how you can express quantitative information! If you want to write to get people to think and act, data visualization minimalism may actively undermine your goals. (highly recommend revisiting chapter 3 with data visualization particularly in mind).
Resources
Things you can use that are easy and free to do some of the stuff described above. Click around and see if anything looks interesting!
Flourish | Data Visualization & Storytelling
Online Diagram Software & Visual Solution | Lucidchart
Free Data Visualization Software | Tableau Public (we are going to do a tutorial on this later on in April!!)
Task
Browse these four data visualizations:
Caffeine in food and drink industry (scroll down for the larger graphic).
Acquisition strategies of tech companies
On Discord, go to # 4-14-data-visualization-lm8 and post the following including this information:
- What visualization best and why?
- What above elements of non-traditional visualization methods were effective do you think? Why?
- Optional: Instead of making your own post, you can respond to someone else’s post if they are talking about the visualization you wanted to talk about. You can agree or disagree (respectfully) by talking about different or similar elements that they talk about.
After posting to Discord, click the button below to continue:
