2012 was a really interesting year for Open Research.
The year started with a boycott to Elsevier (The Cost of Knowledge) , soon followed in May by a petition at We The People in the US, asking the US government to “Require free access over the Internet to scientific journal articles arising from taxpayer-funded research.”. By June we had The Royal Society publishing a paper on “science as an open enterprise” [pdf] saying:
The opportunities of intelligently open research data are exemplified in a number of areas of science.With these experiences as a guide, this report argues that it is timely to accelerate and coordinate change, but in ways that are adapted to the diversity of the scientific enterprise and the interests of: scientists, their institutions, those that fund, publish and use their work and the public.
The Finch report had a large share of media coverage [pdf] –
Our key conclusion, therefore, is that a clear policy direction should be set to support the publication of research results in open access or hybrid journals funded by APCs. A clear policy direction of that kind from Government, the Funding Councils and the Research Councils would have a major effect in stimulating, guiding and accelerating the shift to open access.
By July the UK government announced the support for the Open Access recommendations from the Finch Report to ensure:
Walk-in rights for the general public, so they can have free access to global research publications owned by members of the UK Publishers’ Association, via public libraries. [and] Extending the licensing of access enjoyed by universities to high technology businesses for a modest charge.
The Research Councils OK joined by publishing a policy on OA (recently updated) that required [pdf] :
Where the RCUK OA block grant is used to pay Article Processing Charges for a paper, the paper must be made Open Accesess immediately at the time of on line publication, using the Creative Commons Attribution (CC BY) licence.
By the time that Open Access Week came around, there was plenty to discuss. The discussion of Open Access emphasised more strongly the re-use licences under which the work was published. The discussion also included some previous analysis showing that there are benefits from publishing in Open Access that affect economies:
adopting this model could lead to annual savings of around EUR 70 million in Denmark, EUR 133 in The Netherlands and EUR 480 million in the UK.
And in November, the New Zealand Open Source Awards recognised Open Science fro the first time too.
2013 promises not to fall behind
This year offers good opportunities to celebrate local and international advocates of Open Science.
The Obama administration not only responded to last year’s petition by issuing a memorandum geared towards making Federally funded research adopt open access policies, but is now also seeking “Outstanding Open Science Champions of Change” . Nominations for this close on May 14, 2013. Simultaneously, The Public Library of Science, Google and the Wellcome Trust , together with a number of allies are sponsoring the “Accelerating Science Award Program” which seeks to recognise and reward individuals, groups or projects that have used Open Access scientific works in innovative manners. The deadline for this award is June 15.
Last year Peter Griffin wrote:
The policy shift in the UK will open up access to the work of New Zealand scientists by default as New Zealanders are regularly co-authors on papers paid for by UK Research Councils funds. But hopefully it will also lead to some introspection about our own open access policies here.
There was some reflection at the NZAU Open Research Conference which led to the Tasman Declaration – (which I encourage you to sign) and those of us who were involved in it are hoping good things will come out of it. While that work continues, I will be revisiting the nominations of last years Open Science category for the NZ Open Source Awards to make my nominations for the two awards mentioned above.
I certainly look forward to this year – I will continue to work closely with Creative Commons Aotearoa New Zealand and with NZ AU Open Research to make things happen, and continue to put my 2 cents as an Academic Editor for PLOS ONE and PeerJ.
There is no question that the voice of Open Access is now loud and clear – and over the last year it has also become a voice that is not only being heard, but that it also generating the kinds of responses that will lead to real change.
When a President annouces a scientific project as publicly as President Obama did, the world listens. The US is planning to put signifcant resources behind a huge effort to try to map the brain. There has been a lot said about this BRAIN project , and I have been quietly reading trying to make sense of the disparate reactions that this ‘launch’ had – and trying to escape the hype.
I can understand the appeal – the brain is a fascinating invention of nature. I fell in love with its mysteries as an undergraudate in Argentina and I continue to be fascinated by every new finding. What fascinates me about the discipline is that, unlike trying to understand the kidney for example, neuroscience consists of the brain trying to understand itself . That we can even ask the right questions, let alone design and perform the experiments to answer them is what gets me out of bed in the morning.
Trying to understand the brain is definitely not a 21st Century thing. For centuries we have been asking what makes animals behave the way they do. And yet we still don’t really know what it is about our brains that makes us the only species able to ask the right questions, and design and perform the experiments to answer them?
Many of us neuroscientists might agree that how we think about the brain came about from two major sets of finding. Towards the end of the 19th Centrury it finally became accepted that the brain, like other parts of the body, was made up of cells. It was Santiago Ramon y Cajal’s tireless work (with the invaluable assistance of his brother Pedro) that was fundamental in this shift. This meant that we could apply the knowledge of cell biology to the brain. The second game changer was the demonstration that neurons could actively produce electric signals. In doing so, Hodgkin and Huxley beautifully put to rest the old argument between Volta and Galvani. This meant we had a grip on how information was coded in the brain.
From this pioneering work, neuroscience evolved directing most of its attention to the neurons and their electrical activity. After all, that is where the key to understanding the brain was supposed to be found. Most of what happened over the twentieth century was based on this premise. Neurons are units that integrate inputs and put together an adequate output passing the information to another neuron or set of neurons down the line until you get to the end. In a way, this view of the brain is not too different from a wiring diagram of an electronic circuit.
Trying to understand the wiring of the brain, however, is, not easy. There are thousands and thousands of neurons each with a multitude of inputs and outputs. You can quickly run out of ink trying to draw the wiring diagram, It is because of this complexity that neuroscientists (just like scientists in many other disciplines) turn to simpler models. We have come to know some secrets about learning from studying the sea slug Aplysia, about how the brain gets put together from flies and frogs, and even about how neurons are born in adult brains from singing canaries. What all these models have in common is that we can tie pretty well a very specific aspect of brain function to a circuit we can define rather well. And we have learned, and keep learning, heaps from these models. The main thing we learn (and the reason why these models continue to be so useful and fundamental for progress) is that the ‘basics’ of brains are quite universal – and once we know those basics well, it is a lot easier to work out the specifics in more complex brains.
Trying to understand the architecture of circuits has proven to be of major value (and this is what the connectome is about). But building the connections is not just about drawing the wires – you need to build in some variability – some connections excite while others inhibit, some neurons respond in predictable linear ways, others don’t. And when you are done with that, you will still need to start thinking about the stuff we have not spent a lot of time thinking about: those other cells (glia) and the stuff that exists in between cells (the extracellular matrix). More and more, we are being reminded that glia and extracellular matrix do more than just be there to support the neurons.
So it is not surprising to find some skepticism around these large brain projects. Over at Scientific American, John Hogan raises some valid criticisms about how realistic the ambitions of these projects are given the current state of neuroscience (read him here and here). Other lines of skepticism center around the involvement of DARPA in the BRAIN project (read Peter Freed’s views on that here or Luke Dittrich’s views here). Others criticize the lack of a clear roadmap (read Erin McKiernan’s views here). Others have expressed their concerns that too strong expectations on advancing our knowledge of the human brain will overlook the importance of exploring simpler circuits, something that had been stated clearly in the original proposal .
Is now the right time?
Back in the ‘90’s the decade of the brain had insinuated it would solve many of these problems, I don’t think it did. Despite the neuroscience revolution from about a century ago and the work that followed, we still have not been able to solve the mysteries of the brain.
But this decade is somewhat different. I am reading more and more stuff that has to do with the emergent properties of the brain – not just the properties of the neurons. And for the first time since I started my road as a neuroscientists I am being able to ask slightly different questions. I did not think that successful brain machine interfaces would be something I’d get to see in my lifetime. And I was wrong. Even less did I think I would get to see brain to brain interfaces. But the works is moving forward there too.
The BRAIN project is not alone. In Europe the Human Brain Project received similar attention. We all expect that such boosts in funding for multidisciplinary research will go a long way in making things move forward.
It is inevitable to think of the parallels of the approach to these Big Brain projects and the National Science Challenges – which are wonderfully expressed by John Pickering here.
I think that Erin McKiernan’s cautionary words about the BRAIN project might be quite appropriate for both:
Investing in neuroscience is a great idea, but this is not a general boost in funding for neuroscience research. This is concentrating funds on one project, putting many eggs in one basket.
 Brain Research through Advancing Innovative Neurotechnologies,
 Alivisatos, A. P., Chun, M., Church, G. M., Greenspan, R. J., Roukes, M. L., & Yuste, R. (2012). The Brain Activity Map Project and the Challenge of Functional Connectomics. Neuron, 74(6), 970–974. doi:10.1016/j.neuron.2012.06.006