We're a little crazy, about science!

The big data haul

It’s been one hell of a week and it’s only Monday. Experiment days are always hard, but when you’re doing multiple experiments in one day in, let’s say not so ideal situations, it can be hard. But we’ve made it out the other side! Unfortunately, just because the experiment is over, doesn’t mean things get any easier. At least in this case, because now comes the hard part.

As usual, we should start with what we’re talking about and that my friends is a big idea (here). I don’t want to brag, but it was a really good idea. The problems were many. First, I didn’t have any funding for the idea. Second, we needed help from several different people across departments. Third, we needed some equipment. Lastly, we needed a way to make sense of the data. That last requirement, that’s all me. Because like it or not, I’m the only one qualified enough to make sense of what we are doing.

Since there’s so many different moving parts and the population for the experiment is so small it has been slow going. In fact to date I don’t have a single dataset from the way I initially designed the experiment. It will hopefully happen eventually, but right now it’s good to at least check a few things prior to the big event. The first time is always the hardest, as I mentioned with my dissertation data collection (here)!

However, we’ve had some good luck finding people for the project that aren’t exactly what we want, but close enough that we can at least test my theory. Side note, I know it works, it has to work, it’s physics, you can try, but you can’t fight physics. So really this is just a sanity check before we start collecting the real deal data. Truthfully, I think showing something early on will also help get our collaborators excited about working with us on the project in a more hands on way. So it’s not a bad deal, plus it gives me a chance to start working on some of the code I’ll need for the project. Well projects since there are a few now thanks to big idea.

That said, we had not one, but two chances to get data for big idea. The first time we tried this we failed miserably. It wasn’t that we couldn’t make sense of the data, it was that we had no data. We had perfect line noise and that was all, there was nothing to show for our efforts! I’m still running under the assumption that a cable came disconnected. We were working in a cramped space, had very little time, and there were problems right out of the gate when we attempted it.

Despite having to repeat the first experiment in the same cramped and rushed setting, we managed to do pretty well. I’m fairly confident that we have some data. That’s the good news. It looks like actual data the way I was expecting it to look. At first we had run into some issues, but after troubleshooting I managed to get everything looking the way we would expect it to look. Namely I found the artifact I was looking for, meaning we at least have something to work with. Ideally we’ll have more to show for it than just line noise (electrical noise from the walls, lights, machines, etc.) and that artifact, but we won’t know until I start processing the data.

Since it’s been a rough day, that won’t happen until tomorrow. Shockingly I misread the schedule and thought our second experiment wouldn’t happen until super late in the day, like I would be at the hospital until 8-9 pm late. But that didn’t turn out to be the case so while it’s been a very long day, it wasn’t quite that long.

So while I’m not 100% sure we have something useful, I feel better about the chances of us having something that we can use. If even just one of the two datasets we collected show something other than noise, then we will be well on our way to getting the data I’m really excited about collecting. If not, well then we’ll have to figure out what the heck is going wrong, because clearly there is some issue that I’m not aware of.

With a little luck, I’ll know for sure tomorrow though.

4 responses

  1. Way to keep us in suspense, haha. But I’m glad to hear confirmation that you at least got a little farther than last time. It sounds like you can’t think of any reason for it to fail at this point, so I assume you’re just being cautious because you already got (different) strange results once?

    Liked by 1 person

    May 23, 2022 at 8:51 pm

    • Haha! Yeah I mean it could be data, it could be a new fun error, who knows? That’s the fun of research I guess!

      Liked by 1 person

      May 24, 2022 at 8:11 pm

  2. Since you already had bad data, and this is different, you either have good data or have new and exciting bad data. I like those odds!

    Liked by 2 people

    May 23, 2022 at 9:23 pm

    • Haha that’s exactly my feeling. Either we succeeded or found a new way to fail!

      Like

      May 24, 2022 at 8:11 pm

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