Keeping track of bits and bytes.


The Module One report was possibly the most complicated assignment I've ever had. It pulled data from more places than a high school science fair board, and covered more diverse sources than a literary analysis essay.
The closest I’ve had was maybe a research paper my sophomore English teacher assigned us. She required that we cite several websites and physical books, with in-paragraph citations. I read through all of my sources, made sure they corroborated, and wrote a stellar text that made the individual facts flow together, had great diction, and a note where all the citations would be. Then I realized I didn’t know which fact had come from which source, and I had a sad time combing through texts trying to reverse-engineer my essay.
For this project, I mostly managed to avoid that error by copying facts and sources into my outline. However, every now and then I’d write something and realize it had come from a source other than my experiment. Then I'd have to choose: should I pause what I was working on and abandon my flow to chase down the fact I was weaving in, or keep going and come back to it later?
For this project, I mostly chased down facts. Unfortunately, I usually found other small items that needed corrections. It would have been so easy to submit tour report with the wrong figure numbers referenced in the body text! This meant that it was 10 minutes before I returned to the original paragraph I was writing, and I felt I wasn’t managing my time effectively. To combat that, I started making a to-do list, organized by section of the report, and that helped.
But there was another reason I felt that I wasn’t managing my time effectively: the first twenty times I tried to do data analysis, it took me ten minutes to reorient myself in the data. Both the DSF and PPIase data came in Excel worksheets with averages and triplicates and team data pulled from a sea of numbers, and sometimes I forgot what DSF stood for and why we wanted the second and not the first derivative. I could talk myself through and figure out what exactly each graph meant, but I took a while. That was never an issue for high school science projects; those charts were simple, with data I collected myself (and had only four conditions in triplicate, not nine) in a format I chose.
I understand that I’m just going to have to get used to Excel sheets and non-intuitive formats. I am not the software designer of a bio-instrumentation company; I may collaborate with other scientists and have to adjust to their data collection methods. And I’m not upset about that. It’s just good to know and practice wrapping my mind around new data tables.
I’m also going to have to find the balance between finishing the big things, like an abstract, in one sitting and chasing down tidbits, like citations.

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