I have just come back from a wonderful meeting of the Spanish Terrestrial Ecology Association ( AEET) where I received a prize for contributing towards a more open and reproducible science. I was pleased and honored to share the prize ex aequo with my great friend and renowned scientist Roberto Salguero-Gómez, whom I hope to meet soon in real life to celebrate.
There were other prizes on science communication and promoting diversity, and I think it’s great that AEET has decided to support and recognize efforts to promote the diversity of people doing science, and the diversity of ways to advance science beyond publishing research papers. It’s also nice that AEET got out there to collect nominations for these prizes - it feels good to feel valued and respected by so many friends and colleagues.
In my short speech after receiving the prize I tried to communicate three basic ideas which I wanted to let written down here:
(1) Science is a common good. Despite the hyper-competitive situation we are living in academia, we should not forget we are working towards a common good. This is not (or should not be) a race competition to see who gets to the goal, but rather a collective effort to advance our knowledge and just build a better world.
We should then make sure that incentives are well aligned, and what is good for science is also good for scientists. If open and reproducible science is good for science as a whole, we should also ensure that doing open and reproducible science is good for individual scientists.
(2) The paradox of software in academia. Everyone wants and needs performant software to do their research, but few people and institutions actually support software development in academia. R packages, and scientific software more generally, are simply indispensable to carry out most scientific research nowadays. And yet we grossly fail to support software development and maintenance, and to support the people who work hard to build that software and share it with the world. Heck, we don’t even cite the software we use in our research, so these people don’t even get their deserved recognition (in case you missed it, I tried to contribute my 2 cents with this R package). We should not take for granted that the R packages/scientific software we need are going to be there, always working, if we don’t support their development and maintenance, and especially the people behind it. We can do better.
(3) The importance of education. Most ecologists, at least in Spain, receive a very defficient education in data management, statistical analysis, and programming. Most PhD students start doing research without solid knowledge on how to design good experiments, write code, perform statistical analyses, and interpret evidence arising from the data they collected. This is bad for them, because they struggle to advance their research, and bad for science, as it often leads to weak research.
It is very important that we take training in statistical analysis and programming very seriously. We are slowly making progress, but we are too slow - we could do much better. I think this stems in part from the fact that providing good education is very undervalued in the CV of an academic - at least when compared to getting big grants and publishing glossy papers. We should realise the multiplicative, though indirect, effect of good education on advancing science. If I manage to educate a thousand students on doing good, solid, reproducible research, this is probably going to be such a bigger contribution to advancing science than the papers I manage to publish along my career. So let’s try to provide the best education we can.
I want to finish with a very warm thank you to all the people at AEET who have so generously given their time and efforts to organise such a superb conference. And to all the wonderful people I have met over these years, who have taught me so many things, have supported me, and have just made life so much more wonderful.
Thank you, and all the best
