Committing to the story

For the past few days I’ve been talking about telling a story with your data. Because at the end of the day as a researcher that’s what we do. We do an experiment and, assuming it goes well, we have a story to tell about the result we found and what it means to the people reading the paper. Ideally any good story will have great visuals to add to the story and to help the reader. Which is where I’m still stuck…

Today is the last day for me to get this stuff done because tomorrow hospital-PI will want to see a somewhat finished product. I’ve been doing this a long time now, roughly three years, and even when I first started hospital-PI trusted my judgement. That’s kind of his thing, treat everyone like an equal. This has its benefits and it’s headaches. Being an equal means having power to tell him he’s being dumb and actually effecting change, the downside is that with power comes responsibility.

It means he trusts me to do a good job when I’m tasked with a project and I like to do things unexpected. That’s sort of my thing, try something new and out of the box so to speak. He’s warmed up to my… let’s call it unconventional approaches to projects since we’ve worked together and I think that has a lot to do with my focus on the story we’re trying to tell. It’s also because I’ve taken time to explain how to read the uncommon figures I create and why they are advantageous.

The problem is that sometimes there are multiple stories or different angles to view a project. That occured with my last published first author paper (here). There were a lot of different aspects we could showcase with the dataset we collected and hospital-PI asked me to come up with the story or stories I found the most interesting. From my end, I already know what we hoped to get out of this experiment (ie – the purpose of the experiments we did), but there are several different things we found that I could focus on and all of them feel important.

Some of this story selection is straightforward! Looking at the amplitude changes (referring to the last paper) for example was a no brainer, but the way I displayed the data took time and thought, probably a good week or two before I settled on the chord diagrams. Later in the paper we look at the probability of facilitation at different times and that was a different story to tell and thus we (I) made a completely different graphic to tell that story. Choosing a different style of figure in that case was important too because the chord diagrams I used earlier in the paper wasn’t the best way to display this new data.

What I mean by that is that in both cases, if we removed the text and I sufficiently described how to read the figures (which arguably we did), you would be able to get the idea of what we found. That’s the importance of a good figure and why I like talking about this stuff so much. There are so many different ways to showcase data and some of it is personal preference, but in general I think we can all agree when we see a bad figure. Unfortunately, the differences between a good figure and a great figure aren’t as clear cut. I can write out what makes a bad figure, but I can’t (easily) write out what seperates a good figure and a great one.

Which makes today especially challenging. I have not a lot of time between now and tomorrow, when I’m supposed to show my work to hospital-PI to settle not only on the main story, but the graphics I want to use to tell the story. As I mentioned in the previous posts, I’m probably going to have to play around with a bunch of different options until something catches my eye or makes me happy, but I need to settle on what the main point of story is and is where I’m stuck. Again, I semi-know what hospital-PI is thinking, but since I’m working independently, I need to make sure it’s the correct story, not just the one he thinks we should tell.

As per usual, I can’t talk about the dataset, but what else is new? At least I’m finally publishing stuff so I can share the results now! Anyway, the dataset we have isn’t terribly complex, there’s just a lot of data and a lot of different interactions and things we can compare/contrast. I’m fairly certain on the main story I would like to tell, I’m just not sure hospital-PI feels the same. I guess I’ll find out tomorrow though! There are probably going to be two separate “stories” here that I am going to try to make figures for and that has the potential to be tricky, but only because I need to tie them together and right now it feels disjoint.

To sum up the situation, or maybe just to pass along some advice, spend time thinking about the story you want to tell and how your figures/graphics will aid in that story. You don’t want to create figures blindly because then you have to either try to massage the story to fit the figure or you need to recreate the figure to help tell the actual story you’re trying to tell. It feels like I’m not getting anywhere, but for the past few days when I’ve had time I’ve spent the bulk of it thinking about the story and how to showcase it.

I’m confident I’ll have everything ready to go for tomorrow, I just need to settle on the figure style that best helps my story. Maybe I’m overthinking things, I’m known for that too, but I take this stuff very seriously because I want people to be as excited as I am about the experiments we’re doing.