Summer on a Shoestring

The Drama of a Data Disaster​
December 22, 2017, 12:32 am
Filed under: Uncategorized

Hello! My name is Maddy Morley! I know this is my first blog post, but I assure you it’s because I’m a blog post-slacker… not because I’m new around here. I started working on MELNHE as a fresh-faced high school graduate back in 2015. Now as a 1-semester-to-go grubby undergrad senior at SUNY ESF, I write to you a tale of righting-the-wrong in a drama of a disastrous dataset!

After classes had finished for the semester, I was forced to acknowledge the chaotic mess of 2016 leaf litter data! What’s this you ask? Well, during the fall of 2016, we collected leaf litter from the litter baskets four times. This was a way to look at the differences in the timing of leaf fall among the treatments. Sounds all good and dandy right? Ha! All I’m saying is that includes a lot of paper bags to manage (n= ~ 760)… BUT HOW COOL WOULD IT BE TO SEE WHAT DIFFERENT SPECIES ARE DOING IN DIFFERENT TREATMENT PLOTS?! Super duper cool! Let’s sort the contents of litter baskets by species! Well that my friends, takes an army of high schoolers and undergrads who are paid in pizza and college credit! It took this army an entire year to oven dry and weigh 6 stands, and sort, dry, and weigh 4 more. The sorting by species generated approximately 2,210 coin envelopes/ paper bags. WOWZA! That is a lot of samples and there are lots of ways for this to go wrong…

Labeling errors caused duplicates. Weighing things inside envelopes when they should have been weighed in a weigh boat lead to incorrect masses. Mistakes in writing or typing the weights were problematic. Samples were misplaced, lost, found, fixed, redried, reweighed, and of course, some were ground for nutrient analysis before we could double check them… *sighhhhhh*

Sounds like a lot of work… hurray that my good friends Griffin (aka the man with an eye for errors), Dan (aka the king of sample sorting) and Ruth (aka our fearless leader and scientific mentor) were there to help! After spending seven straight days in the lab, we’ve finally done it! We have fixed the errors and are confident with our data!

What have we learned from this experience?!

1 – Having a plan is key! When I tried to fix the problems early on, I was frustrated with how chaotic the data was. There was a lot of work to do and I wasn’t sure where to begin, but after the team created an action plan, work was accomplished more efficiently.

Screen Shot 2017-12-21 at 7.21.54 PM.png

The action plan board which was written in purple and covered in hearts!


2 – Communication is everything! By talking among team members, we were able to work through the problems together instead of battling them by ourselves.

3 – By setting goals, you can make realities! Before really delving into this problem, I set the goal to finish by Christmas and we did it three days ahead of schedule! We’ve all worked really long days, but it is done!!! And being done my friends is the best Christmas present of all! 😉

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Ruth’s office was transformed into our headquarters and was covered in samples and boxes!


Now I’m off to analyze the data and finish our manuscript! Oorah!





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