This workshop was the first time I ever heard about the concept of Open Science. I didn’t expect it to be all about politics, which is fine for me, but the way the topic was framed seemed very limited. Data reuse and recirculation, together with evaluation metrics for scientific production, were the main two points discussed; quite more related to efficiency than openness, and even for that purpose, severely limited.
I will start by addressing the data circulation efficiency issue. The fact that this decade has been iron-branded by Big Data Analytics is a secret to no one. It is true that immense amounts of data are being produced on a daily basis, with plenty of it being redundant and/or discarded after some light usage. This is a consequence of research decentralization both in the public and the private sectors in which different research institutions work on the same fields in a chaotic, uncooperative way: scientific competition is inherently redundant, and hence inherently inefficient. If we care about the efficiency of our research infrastructure, we should start with proper centralized planning of research efforts. Proposing a whole new internet for machines with the purpose of accessing data a posteriori just because we are unable to give up a selfish, competitive approach to science is just the millionth example of seeking absurdly complex technical solutions to issues that arise from the limitations of an archaic socio-economic system.
Science will never be Open as long as education is not available for everyone, for free. That simple truth was not mentioned once during the day-long workshop. The fact that many students can’t afford college in spite of being good enough for it should be the main concern of anyone claiming science should be open. And the issue doesn’t stop at tuition fees. PhD salaries, that step every young researcher needs to walk through, are notorious for paying below living wage (after a few months working for free awaiting the scholarship, of course). London universities, for the sake of taking an example out of the institutions that attended the workshop, offer the shocking amount of £17000 salaries on their PhD fellowships. Has anyone tried living in London on that budget? Because I have, and it doesn’t work. The result is that the PhD candidates that take the fellowships are the ones that have their parents backing them up economically. And that’s a shame. How can we claim we want Science to be Open when we are disregarding the fact that becoming a scientist is almost entirely determined by the income of the household you are born into? And I’m throwing the ‘almost’ in to account for some insufficient scholarships that do exist.
I do agree with some of the points made during the workshop. Scientific publications should be readily accessible to absolutely everyone (god bless Sci-Hub). Impact factor is very limited and has negative side effects. Those considerations are true. However, focusing on these points while we disregard critical causes of inequality and overall inefficiency feels like discussing the quality of the coffee we are having while the office is on fire.
I will leave uncommented the point about citizen science, a euphemism for «why should we pay scientists their wages when people is willing to do their job for free?” Just pay wages.
Yes, I am an Open Scientist, because I am all for free education and paying scientists living wage. Then, let’s centralize research. Then, the rest.
I almost agreed to what is mentioned here. The only issue that is opened and bit contradictory is how you pay wages to scientists if all education is free in this modern money-driven society?
That opens new issues I suppose…. However I agree to more accessible education, not necessarily totally free. The only motivation for not being completely free I find into the regulation of scientific publications. I personally encountered a numerous plagiarism from authors/ professors from US and Canada. I have reported them, they are still publishing the same article over and over to «good» conferences.