More artistic advice for scientists

Photographer Chase Jarvis came up with the snappy-sounding advice: Create. Share. Sustain. And because original references are important: Originally formulated for the Art Director’s Club of Denver in The Consequences of Creativity.

Chase Jarvis believes that people create photographs in order to share them, and that there is a difference between personal work, and other work. So that, even if you are a professional photographer, most of what you do will be for money and not for the sake of art. This is the sustain part, if you are not a professional photographer maybe you sustain yourself by having a proper another job.

Create:

Coming up with new ideas, designing experiments to test them, and then to run those first experiments, when the method starts working and you get the first indication of whether you can reinforce or disprove your hypothesis. That's the essence of science, and that's where all the excitement lies.

Share:

Publishing is obviously the all-important sharing in science, but it being all-important also puts it firmly in the sustain-phase. Pleasing that third-reviewer, completing those control-groups and trying to fit three years of work into a 250-word abstract is not something you do for fun. The fun part of sharing, the part that actually lets you share your insights, get feedback and learn new stuff, is conferences.

That is where you can (not everyone does, but they could) present your really new data, and hint at ideas for the future and see how your thinking is received by the community. It sharpens your thinking, and brings the field forward. It will often reveal experiments that have already been done but not published, and might warn you off (or reinforce) some particularly difficult hypotheses.

Sustain:

Somewhere in each project's life it goes from being curiosity-driven to being driven by the need for completeness before publishing. Coincidentally this is where it often gets boring, which is why I put finishing up and publishing under the sustain phase. The other thing that is directly science-related that is part of sustaining is grant-writing, and grant-reporting. It is a bore and it takes a huge amount of time, but it is necessary to continue doing research.

Otherwise, sustaining often means teaching, supervising students and treating patients. If you are lucky, you find all of this exciting and entertaining as well, but even if you do, it is time off from research. However, just as in photography this is not only what often pays the bills, it is also a fountain of ideas for future research. Sometimes a question you can not answer may indeed be an unanswered question, and the problems that bother actual patients (or their physicians) keeps you founded in clinically relevant research.

So, there we are. Do some proper work, write some grants so that you can do research and go to conferences where you can drink beer share your findings, and get ideas for more research. Research that will have to wait until you have finished teaching for the semester, and aren't scheduled in the A&E every other night.

Advice from Neil Gaiman

Being a fan of Neil Gaiman's, like apparently everyone else on the planet, I watched his Commencement Address at the University of the Arts in Philadelphia, and I was once again struck by how similar worlds of art and science are. (I'm sorry, that should be Dr. Neil Gaiman.)

Anyway, the good doctor provides some good advice. First he notes that (or not first, but first of what I found particularly interesting) - that more and more art is produced on a freelance basis. That is you produce, and then you try to find buyers, or you put out an idea and find supporters so that you can produce. I think that is a very fitting description of an early science career, and in many ways even of the day-to-day work of established scientists. There are collaborations between scientists, there are grant-funded projects, and there are temporary academic positions, they all have in-common that you have to have a good idea (with some preliminary data), and you only get to continue if you do produce what you say you would. Or something equally awesome.

This above all other points has to be realised by anyone starting out in science, and by anyone in science who hasn't understood it yet: You are only what you bring to the table. The question is what to bring to the table. Neil's advice is simple: Produce good work, be easy to work with, and deliver on time. Pick any two. As he exemplifies if:

"People will put up with how unpleasant you are if your work is good, and you deliver it on time.

People will forgive the latness of your work if it is good, and they like you.

And, you don't have to be as good as everyone else if you are on time, and it's always a pleasure to hear from you."

 -Neil Gaiman

Sadly, this only goes for collaborators, and positions. Our backers in science have largely been dissociated from social interaction, which means that we only have two things to show them: How good our work is, and that it is delivered on time. Pick any two.

Now, if you aren't delivering at least two, you have a problem. It may be ok for a while if your work is really new and really good. However, if you're a chore to work with, your work is middling, and it isn't delivered on time, then you will notice that people aren't working with you any more. This is not because what you are working on isn't interesting. It's because we all hope to be doing this for the rest of our lives, and working with people who can't deliver, or are unpleasant to work with, just isn't worth it. An insight that fits well with the best advice Neil Gaiman ever got:

"You should enjoy it." 

-Stephen King

R-startup scripts

If there are some things you use all the time in R, you might not want to have to load them specifically every time. That is what ~/.Rprofile is for. As a start, have a look at R-bloggers: Customizing your .Rprofile and Customizing R: startup script. Then the question is what to put in your startup-script.

cat("Good morning Dr. Chandra.\n\n", sep = "") is an excellent choice.

As an alternative:
library(lubridate)
if (hour(Sys.time()) < 12)
  cat("\nGood morning Dr. Chandra!\n\n", sep = "")
if ((hour(Sys.time()) >= 12) & (hour(Sys.time()) < 18))
  cat("\nGood afternoon Dr. Chandra!\n\n", sep = "")
if (hour(Sys.time()) >= 18)
  cat("\nGood evening Dr. Chandra!\n\n", sep = "")
is more probable to be correct in a linguistic sense.

Then there are other important things. Like setting the language to English. For some reason R thinks I want it to speak German, even though nothing else on my system is in German. I have given up trying to find out how to fix it properly, so I use: Sys.setenv(LANG = "EN")

As they point out elsewhere though, you shouldn't put too many things in that you actually use for data analysis. That would make your code difficult to follow. It might be anyway, as mine is, but at least all libraries and such are loaded in the R-directory of the specific project. However, I do have a loading option for a .Rbasicfunctions.R:
if(file.exists("~/.Rbasicfunctions.R")){
    source("~/.RbasicFunctions.R")
    cat(".RbasicFunctions.R was loaded, providing the following functions:\n\n",sep="")
    print.functions()}

The actual file is empty though.

The center of the civilised world

That would be London. I am actually back in Uppsala now, but it was the center of the civilised world until Sunday. On the way home from the 22nd ESH meeting at ExCel I stopped at Paddington Station and went for a walk and some grub. Just as street or two away I found Micky's Fish & Chips, which I couldn't resist. To my great delight the fish was excellent, and the chips were chips. All told they just delayed my departure by fifteen minutes. I should have stayed longer, central London is much nicer than Heathrow Airport.

The ESH meeting was not bad either. I met many new friends and kicked off even more collaborations than at EB. I really must say that these meetings just keep getting better as I attend more of them (and have worked longer in the field). ESH suffers a bit from being too many clinicians. Some of the best work was relegated to posters in favour of rather bland clinical trials. That is not all bad, because then you really have time to discuss the data with the authors, and invite them out for a pint, which is actually the most important part of scientific meetings anyway.

The Big Day™

I have been waiting for this day for as long as I have ever waited for anything. In 2001, I and a group of my friends at the Gästrike-Hälsinge Nation (a student club/union in Uppsala) pooled our meagre resources, and bought one bottle of each of the five premier grand cru en primeur. That is, the three houses that produced the best wines in Medoc in 1855, Chateaux Haut-Brion, and Chateaux Mouton Rothschild that was elevated from 2'me Cru in 1973.

But first we had lunch, and to said lunch we had a collection of not-quite-as-illustrious 1999s. First out was Chateaux La Fleur-Petrus, the second-wine of Ch. Petrus (which was too expensive for us already 2001). Second was Ch. Pichon Longueville Comtesse de Lalande, then Cos D'Estournel, Ch. Ducru-Beaucaillou, and the odd-man-out Opus One.

As we always did in 2001, we voted for the best, and worst wine. The least smashing of the lunch-selection was the Ch. Pichon Longueville, and won did Opus One. It wasn't my choice, but it had a clear majority.

The main event, as you have already figured out, was the following wines:

Ch. Haut-Brion 1999
Ch. Margaux 1999
Ch. Lafite Rothschild 1999
Ch. Mouton Rothschild 1999
Ch. Latour 1999

Tasting this kind of mature (they have all reached their maturity-plateau) high-quality wines is very interesting because they change character so quickly when they are exposed to air. At first tasting, I tought Ch. Margeaux was going to be a clear winner. After some fifteen minutes I had changed my mind to Ch. Latour, but when it was time to vote the initally closed Ch. Lafite Rothschild had opened up and received my vote. I was wrong again, and Chateaux Margaux was voted best of the 1999 premier cru classé.