Together with my friend Bine, I’m working on an interactive data visualization, designed to give a general audience a big picture of what’s happening on Earth.
It works by shrinking down the Earth by a factor of 100 million. We picked that factor because it gives nice, memorable numbers, and you can do the conversion in your head. For example, on our “Small World”, there are 81 people, 11 cars, and 7 cats!
We found that after people interact with the page, they often can remember the involved numbers and proportions really well! (Remember the 7 cats? There must be 700 million cats on the real Earth.)
To make the site as helpful as possible, we’d love your feedback on the following questions (either here or in the survey linked at the bottom of the article):
While reading the article, what surprised you the most?
Is there something you felt was missing?
Was something on the website broken or did not work as intended?
Also, feel free to critique our approach, or mention ideas for developing it further!
Small World: Looking for feedback on our data visualization
Together with my friend Bine, I’m working on an interactive data visualization, designed to give a general audience a big picture of what’s happening on Earth.
It works by shrinking down the Earth by a factor of 100 million. We picked that factor because it gives nice, memorable numbers, and you can do the conversion in your head. For example, on our “Small World”, there are 81 people, 11 cars, and 7 cats!
We found that after people interact with the page, they often can remember the involved numbers and proportions really well! (Remember the 7 cats? There must be 700 million cats on the real Earth.)
You can find the project at https://smallworld.blinry.org.
To make the site as helpful as possible, we’d love your feedback on the following questions (either here or in the survey linked at the bottom of the article):
While reading the article, what surprised you the most?
Is there something you felt was missing?
Was something on the website broken or did not work as intended?
Also, feel free to critique our approach, or mention ideas for developing it further!