The data for our data visualization project was pulled from a Googe form survey that was extended to our family and friends through Facebook. At first, we wanted to have a less biased demographic than the predicted college students who live in California, so we tried out Mechanical Turk. However, the results gathered from the survey were not usable due to the vague and/or spam-like answers.

Thus, we got a refund for our survey and decided to use Google forms to reach out to more reliable people who we actually know in real life. Most people who answered the survey were most likely to be people that we interact with most recently and often—I imagine UCLA students, home friends, or family. Otherwise, there were a couple of demographics that we did not recognize personally such as a Native American man aging 45-54. This man was perhaps reached through one of the Facebook groups that the survey was posted on. This more limited demographic circle definitely narrowed the range of comparison that we were hoping to make around different areas and backgrounds, but in place made the data more intimate to our environment and circle of friends.

In the Eyeo 2017 talk by Mimi Onuoha, she highlighted towards the conclusion that all data is made through human choices. This was a reminder to me that, as long as humans are the ones collecting data and observing it with a purpose, there is some degree of influence or unobjectiveness that touches the data as well as the conclusions being drawn from it (if any).

tldr; we had to sacrifice biases/diverse demographics for answers that properly followed instructions.