Some people call it karma, others mojo. I call it the data sink. Not a sink as in a kitchen sink with a drain, but rather a sink in the sense of something towards which things flow. I have a theory that on a given day, there is a finite amount of data to be had in a given research environment. And this data is not evenly distributed amongst the members of said research environment. Rather it is usually distributed between a handful of data sinks. These are the people in a lab who seem to be sucking up all the data while everyone else toils around fruitlessly. Fortunately, these data sinks are not stable and can rotate around from person to person over several days. And once you have a data sink you can keep it going by taking advantage of it, much to the chagrin of your lab mates. In my postdoc lab, this seemed to be certainly true, where someone would have a good run where they would get lots of data for several days, but eventually things started to falter and it would be someone else’s turn to soak up all the available data. Occasionally a couple of people would be having good runs and then it would be truly dismal for everyone else. In the rare occasion where everyone was getting data at the same time –a mega sink– we would hear cries and screams from the lab next door. They would knock on our doors demanding we give them back their data. Once you acquire a data sink, the way to keep it going is to work harder, to keep the data flow steady. As soon as you let up, your sink will dry up and go to someone else. So you should treat your data sink with love.
While not everyone will subscribe to my theory on data sinks, I think there are some valuable lessons to be learned from it. Probably one of the most valuable things I learned as a grad student, was learning to identify data sinks. The time when all of your equipment is working perfectly, all your experimental preparations are healthy, your mental state is groovy, and then it happens. Data starts pouring in. And if it does, it is important to fully ride with it, because you don’t know when something is going to break, and the data flow will stop and you never know when you will get it back. During these times you really have to work extra hard, you can take a break when the data sink dries up. And I find this difficult to impart to my graduate students who will often go home, or to the gym, or to a two-hour lunch, or whatever in the middle of an experiment which has been giving them good data all day. They are basically losing their chance to acquire more data and making their life more difficult in the long run. I have no problem with people having a life, but science seems to work at its own pace and you just have to have a flexible work schedule. I’d rather they stay for an extra few hours and then take off the next day, than to stop a perfectly good experiment midway.
Have you ever experienced a data sink? If so, how have you kept it going, how do you get it back once it goes away? Good data sinks are difficult to achieve, and if you find yourself lucky enough to experience one, good care and feeding of your data sink will ensure a most pleasant and long lasting experience. Let the data flow!