For those of you who know me and have heard me rant on the subject, I get on my soapbox regarding properly documenting your work. This is an especially important skill in research – after all, the goal is to create reproducible scientific experiments – but is something that all areas can work on. We’re all guilty of forgetting to write down a step here or there, or forgetting to write a comment about why we chose a particular parameter. Many times, it’s fairly harmless – I can look back through my lab notebook and be able recreate the thought process that happened for that experiment. But it creates difficulties in institutional memory”, the concept of passing down knowledge to the next set of students and researchers who take over your project when you leave (or are trying to recreate your results).

In the digital age, an additional set of challenges arise. Not only are we writing down details about experiments, often time we’re doing the entire “experiments” digitally. In the lab I’m currently rotating in, we perform functional MRI experiments on rats to gain a better understanding of how the brain is connected in various states of rest and wakefulness. However, acquiring data is only the first step. The real knowledge comes with using image analysis software (often times, custom algorithms that we have written based on the literature) to extract useful information from the fMRI images. We use this to build connectivity maps, model disease processes, and hopefully learn how neural signals interact with other components of hemostasis (this is an exciting topic that I plan to cover another day). You can see how important it is, therefore, to make sure that all of the digital work we do is as effectively documented as the physical work.

But being in the digital world also presents many opportunities to make the process of documentation easier. Platforms such as GitHub allow for easy collaboration and archiving of code, data, and experimental protocols. In 2013, President Obama responded to the need within the research community for institutional memory and established guidelines for sharing data. The NIH, and many field-specific institutions (i.e. the Human Connectome Project for mapping neural data) are producing online databases where researchers can share their data.

While we have all these resources, the biggest challenge is establishing a culture of documenting your work. I’ll admit, it’s not easy to do and I’m as fallible as the next person. It takes extra effort and discipline to ensure that someone else will be able to follow every step of your protocol (digital and IRL) after you’re out of the picture. It was awesome talking to some other grad students in my lab and realizing we’re on the same wavelength. We’re currently working on developing a guidebook for new students to learn how to setup and use GitHub (the version control software of choice at GA Tech). The goal is – if we can instill this culture in new students when they enter the lab, they’ll contribute back to the lab with their documented code, and we might make a small step towards institutional memory.

p.s. – if I can get permission from my PI to do so, I will try to share the guidebook here as well