It is kind of bittersweet--I am just about done with the most interesting of the three. This is data I took 5 years ago that is really exciting, but difficult to interpret. We always intended/tried to get some theoreticians on board to help us figure out why we see what we see, but it never worked out for various reasons. The funding ended, and so did the project, though the results are still interesting and novel 5 years later. So now I am writing it for a really good specialty journal, rather than a top-tier discipline-wide one. I really want the data to see the light of day. I am just about done with the first draft manuscript, mostly cleaning it up to send on to my old collaborators at National Lab. I am falling in love with my old data again, seeing why I always wanted to try to explain it better and try for a top tier journal. At the same time, I clearly need to move on to the things my lab is focusing on, so I am not sad to finally get a publication out of it.
Project #2 is similar--nice data that would have benefited from some additional measurements that were never made. This one should go into a good journal for my field, and I will write it as such, since this is the sub-area in which I am best known. Although this is not a major thrust in my new lab, I need to keep publishing in this sub-area because I will likely find very strong people to write letters in support of my tenure bid in this area. I have one student working on something related, so I am looking to see if there are any last measurements my student can do to improve what I already have.
Project #3 is really ancient--the last data was taken six years ago at the tail end of another project. I don't really need to write this one, but I had two summer (undergrad) REU students who worked on it, one of whom is now in a PhD program. I would like to get it done for them, even though it might not even be worth the effort, and will likely go to a minor specialty journal. I feel guilty enough as it is that I never got around to finishing this up. But data is data, and papers are papers, so I will probably spend a week or so on it. It also seems a shame to have data that tells a complete story (no matter how minor and unimportant to me now) go to waste.
I wonder how many projects like these get lost in the shuffle? How much interesting (and already paid for in money and blood) data is sitting in people's old lab notebooks?