Riddhiman Garge
Maitreya DunhamOur labathon just finished up, and everyone agreed we should do it again! I thought I'd post a few lessons I intend to keep in mind for next time. 1. Give sufficient time to pre-wrangle data. For one of our projects, we spent more time looking for things than doing analysis.
We had actually planned for this by having the pitch meeting back in December, but it ran too close into vacation time. Also, it turned out that it did take multiple people working together to find some things (which was a lesson for everyone on good organization practices!)
2. Plan for hybrid. We have one person who is always remote, so we had planned for this, but it turned out to be useful for multiple people in the lab who had to work from home for various reasons.
Also, it made the morning and afternoon check in meetings more accessible for people who prefer coming in early or late, or who work part time.
3. Have a mix of action items people can work on in teams and as individuals. It was so gratifying to see people get together to learn from each other and tackle a problem. But sometimes it made more sense for one person to break off a chunk of the project to work on solo.
4. Deadlines! We had a check in meeting each afternoon where people could show off their results from the day and discuss problems and next steps. It gave a good target time for having something deliverable, and was satisfying to see how much progress happened in just one day!
5. Rope in collaborators. Probably the most successful project was one we started back when @riddhimankg [twitter handle] was still a grad student with @edward_marcotte. He's at UW now, so was able to do the data pre-wrangling, answer questions and post ideas in our Slack channel, and come to our check in sessions.
Helping him finish analyzing this dataset was really motivating and fun for everyone! We got far enough that we have a reasonable start on a manuscript and made some plans for the future for a co-writing sprint to see if we can bring it all together.
Win-win. For him, it's progress on a project that can't be his top priority now. For my lab, the analysis involved learning several new skills, and it will be (hopefully) relatively quick authorship on a cool paper.
6. How to move forward on the labathon projects is one of the things I will try to think about more carefully next time we do this. It's not a great use of everyone's time if the projects just die again after a week of intense work.
For 2 of the projects, I'm currently writing grants to continue working on them, so even a little bit of progress was helpful for generating preliminary data. Also, just brainstorming with everyone about what could be done in the future has been energizing for grant-writing.
And last one: as PI, try to also clear your own schedule as much as possible. Being a little more "in the trenches" than usual was super nice, and it turned out my institutional memory was necessary to figure out several important details along the way.