Natalie Lamb and the Research Hackathon

I attended my first research hackathon earlier this year, along with 17 other researchers and practitioners, the Freshwater and Citizen Science Research Hackathon, at Oxford Brookes University. The event used water quality data from FreshWater Watch, which had been collected by participants/volunteers from around the world. The collected data included: photographs, a description of land use, bank vegetation, water level, water colour, visible pollution sources, turbidity (using a Secchi tube), nitrates and phosphates (using a colour test). The video below explains the data collection and what Earthwatch, the host for the Hackathon, is doing to preserve fresh water.

At first, I was unsure whether to attend or not because of the amount of time that would be dedicated to work that was not part of my PhD. In the end, I decided to go because I thought I would get quite a bit out of it. I was interested in looking at the catchment side of waters, something which is not my usual field (I normally deal with treated water), because I know it is a vital part of the drinking water treatment process but it is not something I have explored before. I was also interested in the hackathon process, how a fully formed research investigation could start and finish in a few days, something unheard of in PhD research question formation. But I was also interested in how the other participants, some of whom I knew would be more experienced with this process, formed research questions, justified them and then used data to answer them. I thought this would help my PhD the most, to learn from those who are used to doing this.

Some things I learned from the experience:

1. Citizen science can produce so much data! I was surprised by the shear amount of data and all of the people who had dedicated their time to the project. In short, I was very impressed.
2. The data needed much more cleaning than the normal data sets I work with. I should have known this and expected it but I didn't. But, it will make me appreciate my own data sets more in future.
3. I need to learn how to use R. I felt that I wasn't always helpful in my research team because I didn't know the same statistical software as they did. I produced other work but with the limited time-frame for delivering results, very little of my work made the final cut. I think it would have been good for me to know some R. I had expected people to help me learn it but the time pressure meant this was not possible.
4. It is more useful to spend less time working and more time networking and relaxing with the people you are working with. Yes, there is competition between the groups but you will get more out of the experience (and have a better, more positive experience) if you take the time to go to the pub, instead of spending a few extra hours working with the data set.

Would I do it again? Definitely. I would still factor in how much time the hackathon would take up but I honestly think it was a worthwhile experience that I would do again.