I'm preparing material for this week's class on experimental design and data analysis, and I ran across this paragraph which I thought was very interesting:
"The cost of analyzing collected sediment samples usually exceeds that of collecting them. However, the funds for the analysis are wasted if samples are collected at inappropriate locations or do not represent the study area. Further, the proper selection and use of sediment sampling equipment, sample handling, storage and transport are all equally important to the selection of sampling locations. Therefore, about 60% of the time allocated to the sediment sampling should be spent on detailed planning of where and how to collect the samples, including logistics associated with the travel of personnel involved in the sampling, shipping the equipment to the sampling location, and handling, preservation, storage, and transport of the collected samples." - Mudroch and Azcue. 1995. Manual of Aquatic Sediment Sampling. Lewis Publishers, Boca Raton, Fla. 219 pp.
The bold part is my highlight, because I am struck by the authors' estimates of the amount of time to spend planning and doing logistics relative to the amount of time actually doing the science. A lot of weeks, I feel like this is an underestimate of the amount of time I spend planning and abetting science rather than doing it. I'm curious to know whether this ratio of planning + logistics to research is different from one field to another. It seems like a lot of the biomed-type bloggers I read spend a lot more time doing science, but maybe that's because the planning and logistics are done by others (PIs and techs, respectively?).
I'm also curious to know whether we could construct a ratio of the time spent thinking about science, including brainstorming, journal reading, proposal and manuscript writing versus the amount of time collecting and analyzing data. Would that ratio vary by research fields or career stages? Is there an optimum ratio?
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Hmmmm...I'm glad you brought this up. It's something I've thought a lot about and I don't know that I've come to any conclusions.
I'm a grad student in a lab that does NOT use technicians and where the students are solely responsible for their own project and experimental design, even to the point of there being very few inter-lab collaborations. The theory behind this is that we learn the skills necessary to do *everything* ourselves. We are not allowed to get techs to do the nitty-gritty processing of samples even, in hopes that we will become proficient in these techniques so that they are transferable skills.
From this perspective, this management style is pretty effective. I am very proficient at the bench, and I can troubleshoot like nobody's business. However, so much of my time is spent on the nitty-gritty of sample collection and processing that might be better spent on analysis and future planning (assuming I have already gained proficiency at the technique). I think it would be very beneficial to my science to be able to pass these things off to a technician at this point.
While I am solely responsible for experimental design and execution and analysis (and I think that these are all good things!), I find it very difficult to switch gears sometimes, nor do I have as much time as I would like dedicated to *thinking* about the science, analyzing results, reading literature, considering how my findings fit into the big picture, etc. I feel like I am always scrambling to fit some thinking time into my day in between doing stuff that a trained monkey could do if they weren't so damn expensive.
I really do believe that this slows me down at this point. A have another grad student friend in a lab where the PI insists that students get "trained" to do new techniques by their very competent technicians, but who otherwise have the techs do the "mindless" parts of the protocols, so that the students are freed up expressly to read, analyze results, formulate new hypotheses, and be meticulous about experimental design. They know how to do all the techniques, and can do so if the techs get backed up, but are otherwise cultivating the "brain" side of their inner scientist, rather than the "hands".
I suspect both approaches have varying success depending on proclivities of the individuals. We'll have to see how this pans out as we take our next career steps. The other frustration is that comparing students in "hands-training" labs to students in labs were the techs do most of the "hands" work can lead to some pretty skewed perceptions of which students are making better "progress". Students that can use techs have more time to think, and can still have someone else producing data while they do so, therefore it is possible that they get more science done per student unit.
Oh boy, good question. I spend a LOT of time on planning and logistics compared to everything else. Preparation for field work swamps the time we actually spend in the field. Everything from designing the overall study, to deciding exactly where and how to take the samples, to making sure ours plans mesh with the work of others, to finding freezer space for samples once we get home. Then I spend a LOT of time planning exactly what to do with the samples back in the lab. It seems my advisor spends a large portion of her time on planning as well, so I wouldn't say it just because I'm new and learning how to do it.
Like AA, I wish I could have had more help with the nitty-gritty repetitive stuff, since after I did enough of it, I wasn't learning anything and it really took a lot of time.
I'd say at least 60% of my time in grad school has been spent on planning/preparation activities. I think my field is pretty similar to yours, though. Well, I think I do less field work than you, but we're more similar than either of us are to biomed types.
If the field work is sampling then I spend far more time planning than actual field work (unless it takes a lot to get to the site(s), of course) ... but, if it's collecting observations in the field (e.g., mapping, logging section, etc.) then it's quite different. Mapping and other such field work requires a lot more time to ponder the science while you are in the field (at least for me). It's difficult to put numbers on these w/out really sitting down and figuring it out (which I'm not gonna do at this moment). Probably would be a good exercise though.
Of some sort of relevance, one common whinge among bioinformatics workers is experimental scientists asking if their data could be analysed, after they've done the work, rather than approaching us before they start, when we could help with ensuring that meaningful datasets are gathered... (Really people are best to approach the bioinformatics/statistics/etc analysis aspects before writing the grant application, but in my experience it's common to see an "arm waving" argument used in place of a proper check of what's really needed.)
On the broader question at the end of the post, by my own estimates, I spend close to half my time doing backgrounding and finding new contracts. I'm an independent scientist, so this may just reflect that I get more time between contracts than I would like (!), but I'll still say that I think that people underdo this, although it's a reflection of the time pressures on most people. I think most people, given more time, would spend more time looking before they leapt as it were.
If you look at NASA planetary flyby missions, they spend decades designing the spacecraft and instruments, finding the optimal trajectory, working out the best order to run all their experiments in...
And the then all the data is collected in just a few days.
As a design engineer who owns his own business, I estimate I spend at least 60% of my time on logistics for custom projects. Often times the logistics is what impresses the customer. There are probably a handful of companies that can do what they need, but getting it to Alaska and ready for installation in two weeks is what impresses them.
Coming from a totally different perspective (I'm a former biologist, now a medieval historian, an independent scholar at somewhere around middle-grad-student level) I've learned the hard way that I DO need to spend considerable time planning and thinking before I go out to take my "samples."
The case I'm thinking of is a recent trip to Europe to take photos of my sources (artifacts, documents and paintings), most of which have never been published in the detail I need to see. I came home to discover how many opportunities I had missed to capture essential information because I did not think through exactly which things I needed to photograph, from what angles and at what distances, the need for special lighting in some cases, and so forth. I *should* have actually written the whole thing out in the form of a checklist. If I had, I would not have come home to discover that I had managed, for instance, to get excellent photos of _six_ out of the seven beads in a string... so I suspect you've got hold of a universally applicable principle here.
(I also discovered that I hate my camera and need to bring a laptop with me on such trips -- nothing like neglecting to test your equipment in advance.)
In fairness, I spent most of the month before the trip trying to recover from flu, bronchitis and a non-trivial medical procedure, and there was no way I could change the trip's scheduling. But still, I should have known better.
Before I recently retired, I was a field ecologist. Therefore I spent considerable time driving and hiking to study sites. I found it useful to talk into a voice activated recorder while hiking or to turn on a recorder while driving. That way I could finish "mapping" out revisions of my sample plan as I approached an unfamiliar site that didn't quite fit what I had envisioned before hand. On the way out, I could add after-thoughts and non-quantitative data. I also recorded thoughts about possible connections and implications, as well as sudden insights. This was especially important when my research involved a prolonged field trip. The BIG drawback was having to listen to my recordings and transcribe the worthwhile stuff later.
60% sounds high for environmental work (I'd have fieldwork that would take up to 6 months to complete), but really, the more time you sped getting it right before you go out there, the less time you waste with your rental equipment, your yucky weather, your impatient drillers, etc etc.
I absolutely agree with the planning to collecting abservations of the other commentors. But what about the time needed for analysis AFTER you collect your data. Maybe because I work at the confluience of science and engineering I see this aspect often solely neglected/discounted.
It seems that once we build and test/fly our widget most of the engineers think were done (other than to tinker to make it better). But its at that point where my work just starts. We need to find out if it works as designed, if we can actually use the widget, and how we can exploit it. Because this post-flight work isn't as visible or 'active' its often overlooked or discounted. But again, I work in an engineering environment, not a science one.