At first I had some trouble understanding the definition of “flatland”, but after reading the examples I have come to define it as the representation of ideas or data across a 2D space. I was confused because I had a hard time distinguishing between the ideas of the physical flatland, such as the screen or the paper, and the abstract values that were attached to them.

In the reading, there were several points that stood out to me. First, I agree with the idea of small multiples, which is to standardize the representation of data across multiple needed distinctions. It makes sense to keep a representation that changes specifically the points that the data calls to. One downside I do see to small multiples is the difficulty of choosing boundaries or differences that will effectively separate the sections of data into meaningful distinctions. For example, if all of the carbon emissions were vaguely similar, then all the mini graphs would look similar, and there would be less of a point to display all of the mini graphs.

Next, I will comment about tables. I agree with Tufte that tables are a standard and powerful way of communicating data. I find that they are this way because there are often times where two ideas want to be intersected, and tables do that well. However, I find that tables have a weakness when it comes to trying to display a data story with more than a few points. Yes, this could be solved with innovative headers, but at certain point the information becomes too muddled to understand.

His point at the end of the reading regarding chartjunk was interesting on many levels. I didn’t agree when he said that if your numbers are boring, then you’ve got the wrong numbers. Sometimes, numbers can be “boring” and still right. For example, I will read the weather charts even if the numbers are all in the 60’s for the next month, and those numbers are still right. I do agree that there is an established quota for conveying information professionally though, and that the concepts of striking visual design and attention-grabbing formats are not necessary and may even take away from the data.