Plotting
Perhaps we’re simply deficient, but in the McCoy group we can’t look at a massive table of data and instantly understand what it’s telling us scientifically. We know a lot of other scientists with this deficiency, too. So to be kind to those of us deficient in this way, when we get result from our calculations we want to figure out how to present them effectively. There are many contexts where the quality of presentation of the data is just as important as the quality of the data itself. For instance, let’s say you did a massive benchmarking calculation to prove one-and-for-all that the letter T is symmetric about the y-axis. This is obviously a groundbreaking result that will revolutionize science. Now imagine in your paper you only ever display an italic T. That’s not going to be immediately convincing to people.
Obviously that example is tongue-in-cheek, but this kind of thing does happen. People will do tons of work to show something, then present their data in a way that obfuscates their conclusions. Developing an intuition for the best presentation of data takes time and effort. There’s also a lot of bad data presentation out there (I’m looking at you, JET), so just because you saw it in a paper doesn’t mean it’s good. There’s also lots of information out there on good data presentation. We’re not trying to weigh in right now on what you should be doing. We are, however, trying to give you a primer on what you can be doing, since knowing what’s possible to do strongly informs what you ought to do.
And, with some luck, we’ll be able to impart a bit of insight into what we, totally subjectively, feel is good practice.
Here’s the road map: