The importance of how you frame your data
The Washington Post recently published Vegetarian or omnivore: The environmental implications of diet, which examines the argument that meat production and consumption is unequivocally worse for the environment than plants.
The author makes the point that while meat has higher greenhouse gas-per-kg cost than any vegetable, you need a lot more than 1 kg of broccoli to get the same amount of calories from 1 kg of beef. When you look at the cost in emissions per 1000 calories, broccoli is more damaging than pork or chicken (by the numbers).
How you frame your data can skew the conclusions your audience draws. Keep this in mind when you work on ideas and implementation of your mapping project – especially if you do a literal geographic mapping project. Mapping the gross of something (such as the total number of car accident fatalities in a year) vs per capita (like the number of fatalities per 100,000 people) can have very different results. If you map total car accidents, states like California (~2800 fatalities) and New York (~1100) will come out on top because of their population size, and states like Iowa (~360) on the bottom. If you map accidents per person per year, you’ll find Iowa near the top (11.9 fatalities per 100,000 people) and New York realtively low (~6 per 100,000) (source).