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You only have to search for "Research Works Act" or look for the #rwa hashtag on Twitter or follow the increasing number of people signing on to the petitions against RWA. You will see that this piece of intended US legislation, which hasn't even passed yet, is getting everybody with a stake in open scholarly communication up in arms. It's a storm of opposition as activists all over the globe come to the rescue of open access. Given this opposition, it seems unlikely that this legislation will pass. Nevertheless, I'd argue that it is already doing what it is supposed to do: delay the ultimate demise of a parasitic industry. Ironically (or maybe not), Nature Publishing Group, itself a component of this industry, albeit with a clear record of grasping the realities of the current developments, was the only voice calling the legislative stunt for what it is: a distraction (the article itself being a testament to the very keen awareness of NPG about scholarly communication and where it is headed).
The RWA is a distraction that works: for weeks now have open access supporters from all walks of science spent countless hours in opposition to this legislation. All these hours could have been spent developing an alternative scholarly communication system that doesn't require publishers with obscene profits. All these hours could have been spent convincing librarians to withdraw their funds from these publishers by cutting their subscriptions and leave them without their main source of income. All these hours could have been spent investing the saved funds from these canceled subscriptions into a system that hosts and makes accessible all scholarly literature and data via our libraries. Instead, we keep sending money to publishers who use it against us. Isn't this an absurd situation: we take time out of our day to complain about hat corporate publishers do with scholarly funds, while at the same time we keep sending them exactly these funds so the publishers can pay more politicians to write yet new legislation and pay more employees to write incendiary articles to keep us busy? Is nobody else seeing the Quixotesque situation here?
The corporate publishers make an annual profit of about 4 billion US dollars, or just under 11 million every single day of the year. Elsevier, in 2010, made a profit of about 3 million US$ per day. According to MapLight, the contributions to members of the US Congress by Elsevier totaled $306,550 for election cycles 2002, 2004, 2006, 2008, 2010, 2012. In other words, if the resulting RWA only delays Elsevier from going out of business for a single day, the investment in these politicians has already paid off. Thus, it is no surprise that Elsevier has their own, full-time employed 'government relations' officials (i.e., lobbyists) and appears to pay staff to directly write the legislation and the defense of that legislation for the politicians. Every single day their parasitic business model is defended means another 3 million in the pockets of their shareholders.
Hence,from now on, I will try to reduce the amount of opposition to publishers and instead focus my efforts more on convincing librarians to skip commercial publishers altogether and use the funds currently tied up in subscriptions to buy some servers to host all the literature and data.
Let's bring our scholarly communication system back into our hands! Hit the publishers where it hurts: their pocketbooks.
Libraries, cut off corporate publishers from the funds that fuel their anti-science activities and cancel all your subscriptions to journals from corporate publishers!
Posted on Friday 27 January 2012 - 12:09:56 
comment: 0
comment: 0| rwa publishing publishers libraries distraction profits |
The first talk by Daniel Geschwind walked us through some of the main features of genome-wide association studies with regard to psychiatric disorders such as autism. Their experimental approach includes using human fetal neurons and looking, e.g., at their gene expression profiles over several time points. What they, perhaps not surprisingly, found was that many of the genes up-regulated during development are associated with psychiatric disorders. He went on to tell us about Weighted Gene Co-Expression Network Analysis which provides an estimate of which genes are co-expressed with regard to their expression levels. Essentially, this technique seems to be a correlational analysis of gene expression profiles over time and grouping those genes the expression of which co-vary over time. One such analysis showed that genes associated with autism are five times more connected than average. In another study they used post-mortem samples from autistic patients (three candidate regions). Using gene expression analysis, they could predict which sample came from an autistic brain and which from a control brain, indicating that there is a shared molecular signature in a subset of autism cases. Another result from this study was that a strong differential pattern of gene expression in different brain regions found in control brains was lost in autistic brains. Looking at which genes are the ones most contributing to these effects, they found evidence that microglia upregulation is involved in autism and that this upregulation might be involved in synaptic formation/pruning in the developing brain. The interesting part of this talk for me was that the genetic heterogeneity of autism spectrum disorders might possibly be reducible to a relatively small set of common molecular pathways and networks.
The second talk by Daniel Weinberger was about schizophrenia. The talk started out with some data on identical twins where only one individual had schizophrenia. From samples such as these, they estimate the genetic risk for schizophrenia. The genes they find also map on general cognitive development. They combine these genetic studies with fMRI to establish connections between genetic information and brain activity. They found that genetic risk factors for schizophrenia are linked to inefficient processing during cognitive tasks - in schizophrenics and their healthy siblings. One point he stressed from his studies was that information processing in the brain is subserved by distributed, degenerate networks. He told the story of a transcription factor, ZNF804a, which had previously discovered to be involved not in any specific region activating during a cognitive task or not, but in how well prefrontal activity was coupled to hippocampal activity, in schizophrenia. Mirroring the degenerate netowrk actions in the brain, he told us that even simple behaviors are subserved by complex, degenerate genetic networks. Not surprisingly, he emphasized the important role of epistasis in such genetic networks. So far, everything he said was right down my alley
To my great pleasure, he even quoted the PNAS paper I shared on Google Plus recently. He went on to rattle through a whole bunch of genes which are involved in associative learning and hippocampal synaptic plasticity and part of a genetic network. None of these genes by themselves scores on risk for schizophrenia. However, the gene-network does score highly on genetic risk for schizophrenia. This means that risk factors in individual genes can be compensated for by the degeneracy of the network. However, when the whole pathway is affected due to several hits in this pathway, the buffering capacity of the network is severely challenged and schizophrenia might result. This pattern was also found in the three genes NRG1-ERBB4-ACT1: individual genes and pairs of genes had low to moderate risk for schizophrenia, a genome with all three risk-associated genotypes had a 27-fold increase in risk for schizophrenia.These first two talks were excellent examples of how the genetic variability in humans is starting to look more and more like nature's way to do genetic manipulations for us that we otherwise would introduce artificially in our genetic model systems. Given the access to huge samples of individuals, this area of research looks very promising and will have a great future.
Albert Galaburda, in the third presentation of this session talked about developmental dyslexia. In contrast to the previous talks, there seem to be reasons to believe that a candidate gene approach might be fruitful. The genes he talked about were Dyx1c1, Kiaa0319 and Dcdc2. Two phenotypes of a Dyx1c1 knock-out in mice are hydrocephaly and situs inversus (organs being formed on the wrong side of the body). These phenotypes share a common underlying phenotype, ciliopathy. Apparently, ciliary action is required to establish asymmetric organ formation (e.g., having the heart on the left side) and to establish a normal flow of spinal fluid. These phenotypes could be linked mechanistically to some of the processes thought to underly developmental dyslexia.
The final talk of this session Allan Reiss talked about Fragile X and Williams Syndrome, two disorders with opposite social phenotypes. After showing us some very interesting videos with patients, he told us a little about the underlying genetics. In Fragile X the responsible gene is FMR1 , encoding an mRNA binding protein, binding mRNAs involved in synapse formation. In Willimas Syndrome, there are 26-27 genes deleted on chromosome 7. The behavioral phenotypes are essentially opposite: Fragile X patients avoid eye contact, while Williams patients seek eye contact, exceeding healthy controls. In Fragile X, social anxiety is lager than non-social anxiety, while in Williams syndrome it's the opposite. However, both groups have high levels of anxiety. In language, Fragile X patients are delayed while Willliams patients are enhanced. Both groups show an enhances stress response. There were some more features I couldn't write down fast enough. Neuroanatomical phenotypes include larger brains for Fragile X patients and smaller for Williams. In Fragile X the frontal cortex is smaller than normal, while in Williams it's slightly larger. The Superior Temporal Gyrus is smaller in Fragile X and larger in Williams. The caudate is much larger than normal in Fragile X while it is smaller in Williams syndrome. In Fragile X, the amygdala is small, while in Williams it's large. Moving on to functional imaging during tasks involving faces, he showed that amygdala activation to faces is increased in Fragile X but decreased in Williams with opposite activations in the fusiform cortex. Prefrontal cortex is activated more in Williams syndrome and less in Fragile X. All these neuroanatomical and neurofunctional phenotypes are obviously very consistent with the behavioral phenotypes.
Posted on Thursday 26 January 2012 - 11:31:19 comment: 0
comment: 0| wcbr schizophrenia autism fragile x williams syndrome dyslexia |
I missed the beginning of Bruce Hope's presentation who was talking about electrophysiological changes in accumbal neurons after repeated cocaine exposure, so I wasn't able to follow the rest of the talk.
Next up was Garret Stuber who is using optogenecis to study natural rewards in mice. Nucleus accumbens (NA) neurons receive dopaminergic input from the ventral tegmental area (VTA) and glutamatergic input from the amygdala, mPFC and hippocampus. Local interneurons are cholinergic. NA neurons can be divided into thse with a D1 receptor and those expressing D2 receptors. Garret's lab uses optogenetics (channelrhodopsin) to drive activity in projection neurons in the basolateral amygdala (BLA). These projection neurons target the NA and if they shine light (using chronically implanted light guides) onto the NA where these projection neurons terminate, they can elicit spikes in the postsynaptic NA neurons. Mice readily learn to nose-poke for such light-induced BLA to NA stimulation, indicating reinforcing properties of this connection. Interestingly, these reinforcing properties are dopamine-dependent, mediated by D1 receptors. He didn't mention where this dopamine would be coming from, given that the projection neurons he was targeting were glutamatergic and I don't know why he didn't first use a glutamate antagonist to see of that would block the reinforcing properties of the light stimulus (upon my question he said that they has done it and that the antagonist had not eliminated but strongly attenuated self-stimulation). They also expressed halorhodopsin in these BLA projection neurons, leading to an inhibition of these neurons upon light stimulation. They used a classical conditioning paradigm to test the effects of this inhibition. Inhibiting these neurons with light during CS presentation prevented acquisition of the conditioned response. They also transfected mPFC neurons with channelrhodopsin. This mPFC to NA connection is not reinforcing. One reason may be that this connection releases less glutamate in the NA, but I did not have the impression they know a lot of what is going on there, yet.
Next up was Gwendolyn Calhoon looking at spontaneous activity in medium spiny neurons (MSNs) in the ventral striatum. This spontaneous firing is called the 'up-state' of the neurons, while silent MSNs are in the 'down-state'. MSNs in the down-state are not only generally silent, they are also very difficult to activate. One may then hypothesize that the transition between up- and down-states functions as a gate to allow input to propagate through the striatum. In her experiments, Gwendolyn is looking at NA MSNs receiving input from mPFC and hippocampus. She finds that mPFC input to these neurons can block transmission of hippocampal input, as long as the mPFC and hippocampal input arrive sufficiently close in time (first mPFC then hippocampus at 50 ms). The mPFC input needs to come in a high-frequency train in order to be able to block the hippocampal response in the MSNs. She found similar results when replacing hippocampal input with thalamus input. This inhibitory effect is specific to mPFC input, as reversing the protocol such that a train of input from the hippocampus precedes mPFC input, has no blocking effect. The mPFC-mediated suppression of hippocampal input is dependent on GABA-a receptors.
Final speaker in this morning session was Michael Cohen talking about electrophysiological experiments in humans. The focus of his research lies in the medial frontal cortex (MFC). His main techniques are EEG and MEG. He finds that negative performance feedback increases MFC oscillations in the theta range. He also used deep brain stimulation of the NA as a treatment option for depression and obsessive-compulsive disorder. Besides being an effective treatment, the researchers also use the implantation for some basic research, by using the stimulation electrodes as recording electrodes for several days between two subsequent surgeries. These electrodes can only record the local field potentials at the location of the electrode. They subject the patients to a reversal learning paradigm where one cue is first associated with reward while another is not and then the roles of the cues are reversed. Reversal learning is often used as a measure of behavioral flexibility. There occurs negative performance feedback in these experiments and they find that theta-band oscillatory synchronization between the two NAs was strongest for trials in which the patients received such negative feedback, dovetailing with the MFC EEG results (the MFC is providing input to the NA). This data can be interpreted as a shift from regional synchronization to more global synchronization after negative feedback. This hypothesis is supported by an increase in MFC-NA synchrony after negative feedback as measured by a combination of EEG with deep electrode recording. The same technique was used in a different behavioral paradigm, where the patients were asked to press a button as quickly as possible, but have been signaled whether or not this press will lead to a reward or not. A large caveat of these studies is that all of these experiments are performed on patients, meaning that something in thier brain is not functioning properly and it is difficult to know how the disorder is influencing the results obtained. Therefore, a combination of two noninvasive techniques in healthy subjects is preferred: EEG with MRI. The used EEG to determine a seed region in the brain which is likely to be responsible for the recorded EEG activity. The seed region was then used in MRI to study the connectivity of this seed region with other brain regions. They found that fronto-striatal connectivity supports error-related theta activity recorded by EEG.
Posted on Wednesday 25 January 2012 - 11:27:04 comment: 0
comment: 0| wcbr nucleus accumbens prefrontal cortex amygdala hippocampus optogenetics |
In the first talk of this afternoon session at the Winter Conference on Brain Research (WCBR) Jeff Beeler showed data that hyperdopaminergic dopamine transporter knock-down mice (which have increased dopamine levels) don't distinguish between two different lever where one lever gives a reward after a few presses and the other requires a lot of presses for a food reward. Wild type mice, not surprisingly, prefer pressing the 'easy' lever. However, if the levers are switched, the DATkd mice show that they can distinguish between the two levers, so it's not that they can't distinguish between the easy and difficult lever. Instead, dopamine seems to affect the motivation of the mice to press the levers in general. Interestingly, these mice were all tested in their home cages and the food reward they obtain by pressing the levers is the only food they get. This difference in motivation is expressed in DATkd mice eating fewer meals per day, but these meals were larger in size than those of wild type mice. These differences in meal-patterns cancel each other out such that total energy consumption is about equal between the two strains. In conclusion, the data presented here suggests a hypothesis according to which increased dopamine levels seem to favor energy expenditure as well as how this expenditure is distributed. It is the latter point where value comes in, the factor where dopamine had been initially associated with. At the very end, he showed a Drosophila ADHD model: hyperdopaminergic fmn mutant flies.
Next up was Sean Ostlund, a former graduate student of my colleague and friend Bernard Balleine. He started his talk by showing examples of motivating cues influencing behavior. Sean uses instrumental conditioning to get animals to learn the incentive value of a cue. Rats press levers for a food reward in the presence of a second cue (in addition to the lever). Because of the confusion of operant classical processes during such learning, Sean is also using Pavlovian-Instrumental transfer: first he pairs a cue (a tone) with a feed reward and then tests how often the rat will press the lever in the presence of that Pavlovian cue. Dopamine receptor blockade abolishes this transfer effect. It gets a little bit more complicated when they use two cues (tone or light) with two rewards (sugar or food) which have previously been associated with the left or the right lever, respectively. Upon presentations of each cuw, the animals then go to the appropriate lever. Blocking dopamine transmission using Flupenthixol (dopamine receptor antagonist) resulted in the rats pressing both levers very little, but still differentiating between the two levers. So dopamine is involved in cue-dependent action invigoration in this paradigm, but not in action selection. Or, as Sean puts it, dopamine provides the 'push' but doesn't 'steer' the behavior, at least in these experiments.
The third speaker was the organizer of this session, Paul Phillips. He started by explaining the difference between model-based and model-free learning. He went on to show an instance of Model-free learning, the Rescorla-Wagner model. Dopaminergic neurons are known to fire according to the prediction-error in this model: whenever the expectation of reward is exceeded, dopaminergic neurons fire more, when it is not reached, they fire less. After these classical experiments, he went on to show operant experiments, where rats had to press one of two levers that would give either a large or a small reward. Pressing the lever for the large reward leads to more dopamine release than pressing for a small reward. In the next experiment, one lever provides water and the other food. Selective satiation (on either food or water) will then bias lever-pressing towards the lever providing the non-devalued reward. When measuring dopamine release, it follows the bias of the animal: the devalued lever leads to less release than the non-devalued lever. In my eyes, he showed two different experiments (operant and classical), but tested the same thing: dopamine responses to cues: explicit cues in one case and the lever in the other. No surprise they don't find any difference. He then showed some more data on dopamine invigorating responding if the animals had only one of the levers and they tested whether or not the animal would reject pressing it. In his model, action selection happens in prefrontal areas and the ventral tegmental area provides dopamine to the nucleus accumbens, where both system project to. Dopamine there invigorates whatever the action selection system selected. This model acknowledges my comment above that dopamine is not directly involved in the operant (action selection) process, but rather in the process of attributing value to external stimuli. In that way this talk dovetailed nicely with Sean's talk.
Final speaker of this so far excellent session was Saleem Nicola. He started by showing that high-effort tasks are disrupted more by dopamine depletion than low-effort tasks. He went on to his experiment of an FR8 task (eight lever presses yield one food reward) where he is looking at the behavior during the inter-press intervals in the presence and absence of dopamine antagonists. What he found was that intervals in which the animals leave the lever for a distance of more than 4cm become longer after administration of a dopamine antagonist. He then looked at the interval the animal needs from pressing the lever to moving towards the reward receptacle and the much longer interval between getting the reward and pressing the lever the next time. The first interval was unaffected by dopamine antagonists and the second interval was increased. Two more experiments showed that a simple dopamine-effort relation can be ruled out. He deduced from these experiments the hypothesis that dopamine receptor activation in the nucleus accumbens core is required for 'flexible approach', i.e., when different actions are required to reach the reward. Recording from neurons in the accumbens (onto which dopaminergic neurons project), he found that their firing encoded future movement latency: high frequency firing preceded fast approach initiation, while low frequency predicted slow (long latency) approach. His conclusion was that dopamine invigorates reward-seeking by enabling accumbens neurons to encode reward prediction. This encoding drives a short-latency flexible approach behavior.
After a hellish 26h hour journey I've finally arrived at the 45th annual Winter Conference on Brain Research. For those not familiar with the concept of these conferences: you have a session in the morning from something like 7-9am then there's a break until about 3pm, when the next sessions start which will last until about 10pm or so.
I registered for the meeting, had a look at the program and decided I first need to catch up with the pile of work that accumulates when you're not online for >24h. For the afternoon session, I'm looking forward to the posters and the session on dopamine and value-guided decision-making.
My own session will be on Thursday at 4.30pm on invertebrate decision-making and I'll be talking about the involvement of PKC and FoxP in flies' decisions to fly to the left or to the right.
Posted on Tuesday 24 January 2012 - 11:06:30 comment: 0
comment: 0| meeting winter conference brain research wcbr |
Today is the deadline for the White House OSTP RFI of digital data and due to this time constraint I have generated my answer largely (but not exclusively!) from copying and pasting parts of John Wilbanks' and Kitware's responses. Now you should go and send them your response as well, they're expecting it and Open Access depends on it!
To (1):
First, Standards should be developed that can be used to grade data sharing plans, so that grant review panels can know both whether or not a specific data sharing plan is satisfactory and so that for any given call for submissions the reviewers have a sense of how important data sharing is versus the scientific goals of the project. Second, data sharing plans should be made public alongside the notices of awards and contact information for the principal investigators, so that both taxpayers and scientists know what promises were made and how to contact a scientist and ask for data under the plan approved.
Third, tracking should be possible to begin to estimate compliance: annual grant review forms should contain fields where the researcher is obliged to place URLs to data shared under the plan (or if left blank, explain why), for example. It should also be easy to create a data request system in which those asking for data send a copy of their request to the grants database, which can then be cross-referenced against the review forms to provide at least a rough estimate of compliance. And fourth, scientists with a record of subpar execution against data sharing plans should be downgraded in their applications for new funding. Taken together, these four elements create an incentive structure that would significantly increase the incentive for scientists to provide public access to the digital data resulting from federally funded research.
In tandem, the funding agencies might develop financial models for the preservation of these digital data in much the same way that models exist for estimating overhead and other baseline costs as a percentage of the grant. This could fund not only new library services and jobs in the research enterprise but also serve as a non dilutive funding source for a new breed of data science startup companies focused on preservation, governance, querying, integration, and access to digital data.
To (2):
In addition to the stakeholders listed in this question, it is critical to note that the general public is one of the primary (if not the primary) stakeholders to be considered here. Given that in the context of federally funded scientific research, it is the public’s tax dollars that are paying for the scientific research being undertaken, and thus the public’s interest is the first one that should be considered when making trade-offs between available options.
Scientists who gathered data in federally funded scientific research did so as part of their job duties, and therefore under U.S. copyright laws they were performing “work for hire.” This means that their employers are the copyright holders of any creative aspect of that data gathering (as pointed above, that only include the organization of data collections). Given that the scientists’ employers received funds from the federal government, it should be expected that they will be subject to the same demands of the Federal Acquisition Regulations (FAR) as other contractors of the federal government. In particular with respect to the licensing of data acquired as part of federal contracts.
Some of the best examples of proper licenses are:
Federal agencies should identify a set of licenses that ensure the rights of the general public to deal with the data, in particular to copy, distribute, and create derivative works, and in this way ensure that the data get to reach their maximum economic potential to foster the growth of the economy.
To (3):
Working groups should be established for different disciplines, involving representatives of leading research institutions for each discipline.
Working groups should define differences with how the data are represented, indexed, stored and exchanged, but should not have the latitude to restrict in any way the free dissemination of information. All the policies should consistently have as a common factor the requirement for immediate and full release of data, unconstrained by any embargo periods or licensing restrictions. Credit for the acquisition of data could be ensured by data publications (eg http://datacite.org) that can be cited by further works.
In this process, it is vital to invest in and commit to the emergence of standards that enable interoperability of, and thus reuse of, digital data. Standards lie at the heart of the Internet and the World Wide Web, and together lower the cost of failure to such a low point that companies built on the web and the internet can begin in garages. Such is not the case in the sciences. And it will not spontaneously emerge, even if data flow onto the web. As long as those data are in a tower of babel of formats, incoherent names, and might move about every day, they will be a slippery surface on which to build value and create jobs. Federal policy could call for a standard method for providing names and descriptions both for digital data and for the entities represented in digital data, like the proposed standard of the Shared Names project at http://sharedname.org .
Standards also make it far easier to provide credit back to scientists who make data available, as well as increasing the odds that a user gets enough value from data to decide to give credit back. Embracing a standard identifier system for data posters will make it easier to link back unambiguously to a researcher as well as to make it easier for grant review committees and universities to receive a full picture of a scientist’s impact, not just their publication list.
To (4):
The working groups in the different disciplines (from Question 3) should establish guidelines on practices for dissemination and storage for different types of data. For example, in genomics, it may be reasonable to store the secondary sequence information but not the primary sequence (given their great difference in data size). Analogously, the guidelines may require primary sequences to be stored only for 2 years, while the secondary sequences should be stored for 10 years.
In astronomy it may be required that certain types of images be stored for different periods of time. Some images may be required to be stored with different compression ratios, and therefore correlate their storage cost with the potential expected benefit for future studies. In this cost-benefit evaluation, the original cost of acquiring the data should be taken into account. For example, a project that invested $50M in acquiring data should not attempt to make savings of a few hundred dollars in storage.
Economists must be involved in the working groups charted with the mission of providing guidelines for storage and dissemination, given that this is a problem in which the trade-off for the benefit of society at large must be continually evaluated.
The policies of federal agencies should be affected by the constant advances in storage technology and the rapid decrease in the cost of storage. The federal government should stimulate the development of storage technology, either by creating large storage decentralized facilities, creating consortia to manage data storage services, involving the public in facilitating distributed (and redundant) storage systems based on peer-to-peer technology that has already proven to handle large amounts of data.
All these guidelines should be prepared following open and transparent procedures in order to prevent proprietary standards and vendor lock-in situations that would prevent the policies from maximizing the utility of federally funded scientific research to the general public.
To (5):
If the policies suggested above are implemented, all stakeholder will have sufficient incentives to implement data management plans.
To (6):
Preserving and making digital data accessible is closely related to the issue of preserving and making scientific publications accessible. If libraries and other non-profit organizations take over these tasks from the current commercial publishers as suggested in my answers to the RFI on scientific literature, there will be more than enough funds available from the current publisher profits to allow libraries to store and make digital data publicly accessible.
Once data and literature are stored in a database where both are linked semantically, innovators have a bounty of opportunities to provide commercial services and develop new applications and drugs/therapies to then generate a profit from.
In the current system, this information is restricted to a small set of academics, with innovators largely barred from access.
To (7):
For existing data, researchers, innovators and other stakeholders will demand compliance from the data stewards and provide feedback for improvements.Compliance with the policies for making the data accessible as it is being generated can be achieved as described above, by developing proper data tracking technology.
To (8):
Once all data and literature are available to innovators, market forces should be allowed to take over without any additional policy interference, as the government is already funding the establishment of this resource.
To (9):
A combination of attribution meta-data and an attribution system awarding attribution scores to researchers. A commonly defined set of metadata annotations will facilitate tagging data with identifiers that point to funding source, researcher name, research lab, institution, and other key attribution information.
Publication venues should in their turn, when considering articles for publication, require researchers to disclose if they used data from third parties, and if so, to provide the proper attribution using the standard annotation identifiers corresponding to that third-party data source.
Researchers would then be able to accumulate attribution scores not only for publications and their citations as is done today, but also for generating data and their use and re-use.
I'm not sure I'm competent to provide expert answers to questions (10)-(13).
First, Standards should be developed that can be used to grade data sharing plans, so that grant review panels can know both whether or not a specific data sharing plan is satisfactory and so that for any given call for submissions the reviewers have a sense of how important data sharing is versus the scientific goals of the project. Second, data sharing plans should be made public alongside the notices of awards and contact information for the principal investigators, so that both taxpayers and scientists know what promises were made and how to contact a scientist and ask for data under the plan approved.
Third, tracking should be possible to begin to estimate compliance: annual grant review forms should contain fields where the researcher is obliged to place URLs to data shared under the plan (or if left blank, explain why), for example. It should also be easy to create a data request system in which those asking for data send a copy of their request to the grants database, which can then be cross-referenced against the review forms to provide at least a rough estimate of compliance. And fourth, scientists with a record of subpar execution against data sharing plans should be downgraded in their applications for new funding. Taken together, these four elements create an incentive structure that would significantly increase the incentive for scientists to provide public access to the digital data resulting from federally funded research.
In tandem, the funding agencies might develop financial models for the preservation of these digital data in much the same way that models exist for estimating overhead and other baseline costs as a percentage of the grant. This could fund not only new library services and jobs in the research enterprise but also serve as a non dilutive funding source for a new breed of data science startup companies focused on preservation, governance, querying, integration, and access to digital data.
To (2):
In addition to the stakeholders listed in this question, it is critical to note that the general public is one of the primary (if not the primary) stakeholders to be considered here. Given that in the context of federally funded scientific research, it is the public’s tax dollars that are paying for the scientific research being undertaken, and thus the public’s interest is the first one that should be considered when making trade-offs between available options.
Scientists who gathered data in federally funded scientific research did so as part of their job duties, and therefore under U.S. copyright laws they were performing “work for hire.” This means that their employers are the copyright holders of any creative aspect of that data gathering (as pointed above, that only include the organization of data collections). Given that the scientists’ employers received funds from the federal government, it should be expected that they will be subject to the same demands of the Federal Acquisition Regulations (FAR) as other contractors of the federal government. In particular with respect to the licensing of data acquired as part of federal contracts.
Some of the best examples of proper licenses are:
Federal agencies should identify a set of licenses that ensure the rights of the general public to deal with the data, in particular to copy, distribute, and create derivative works, and in this way ensure that the data get to reach their maximum economic potential to foster the growth of the economy.
To (3):
Working groups should be established for different disciplines, involving representatives of leading research institutions for each discipline.
Working groups should define differences with how the data are represented, indexed, stored and exchanged, but should not have the latitude to restrict in any way the free dissemination of information. All the policies should consistently have as a common factor the requirement for immediate and full release of data, unconstrained by any embargo periods or licensing restrictions. Credit for the acquisition of data could be ensured by data publications (eg http://datacite.org) that can be cited by further works.
In this process, it is vital to invest in and commit to the emergence of standards that enable interoperability of, and thus reuse of, digital data. Standards lie at the heart of the Internet and the World Wide Web, and together lower the cost of failure to such a low point that companies built on the web and the internet can begin in garages. Such is not the case in the sciences. And it will not spontaneously emerge, even if data flow onto the web. As long as those data are in a tower of babel of formats, incoherent names, and might move about every day, they will be a slippery surface on which to build value and create jobs. Federal policy could call for a standard method for providing names and descriptions both for digital data and for the entities represented in digital data, like the proposed standard of the Shared Names project at http://sharedname.org .
Standards also make it far easier to provide credit back to scientists who make data available, as well as increasing the odds that a user gets enough value from data to decide to give credit back. Embracing a standard identifier system for data posters will make it easier to link back unambiguously to a researcher as well as to make it easier for grant review committees and universities to receive a full picture of a scientist’s impact, not just their publication list.
To (4):
The working groups in the different disciplines (from Question 3) should establish guidelines on practices for dissemination and storage for different types of data. For example, in genomics, it may be reasonable to store the secondary sequence information but not the primary sequence (given their great difference in data size). Analogously, the guidelines may require primary sequences to be stored only for 2 years, while the secondary sequences should be stored for 10 years.
In astronomy it may be required that certain types of images be stored for different periods of time. Some images may be required to be stored with different compression ratios, and therefore correlate their storage cost with the potential expected benefit for future studies. In this cost-benefit evaluation, the original cost of acquiring the data should be taken into account. For example, a project that invested $50M in acquiring data should not attempt to make savings of a few hundred dollars in storage.
Economists must be involved in the working groups charted with the mission of providing guidelines for storage and dissemination, given that this is a problem in which the trade-off for the benefit of society at large must be continually evaluated.
The policies of federal agencies should be affected by the constant advances in storage technology and the rapid decrease in the cost of storage. The federal government should stimulate the development of storage technology, either by creating large storage decentralized facilities, creating consortia to manage data storage services, involving the public in facilitating distributed (and redundant) storage systems based on peer-to-peer technology that has already proven to handle large amounts of data.
All these guidelines should be prepared following open and transparent procedures in order to prevent proprietary standards and vendor lock-in situations that would prevent the policies from maximizing the utility of federally funded scientific research to the general public.
To (5):
If the policies suggested above are implemented, all stakeholder will have sufficient incentives to implement data management plans.
To (6):
Preserving and making digital data accessible is closely related to the issue of preserving and making scientific publications accessible. If libraries and other non-profit organizations take over these tasks from the current commercial publishers as suggested in my answers to the RFI on scientific literature, there will be more than enough funds available from the current publisher profits to allow libraries to store and make digital data publicly accessible.
Once data and literature are stored in a database where both are linked semantically, innovators have a bounty of opportunities to provide commercial services and develop new applications and drugs/therapies to then generate a profit from.
In the current system, this information is restricted to a small set of academics, with innovators largely barred from access.
To (7):
For existing data, researchers, innovators and other stakeholders will demand compliance from the data stewards and provide feedback for improvements.Compliance with the policies for making the data accessible as it is being generated can be achieved as described above, by developing proper data tracking technology.
To (8):
Once all data and literature are available to innovators, market forces should be allowed to take over without any additional policy interference, as the government is already funding the establishment of this resource.
To (9):
A combination of attribution meta-data and an attribution system awarding attribution scores to researchers. A commonly defined set of metadata annotations will facilitate tagging data with identifiers that point to funding source, researcher name, research lab, institution, and other key attribution information.
Publication venues should in their turn, when considering articles for publication, require researchers to disclose if they used data from third parties, and if so, to provide the proper attribution using the standard annotation identifiers corresponding to that third-party data source.
Researchers would then be able to accumulate attribution scores not only for publications and their citations as is done today, but also for generating data and their use and re-use.
I'm not sure I'm competent to provide expert answers to questions (10)-(13).
With roughly four billion US$ in profit every year, the corporate scholarly publishing industry is a lucrative business. One of the largest of these publishers is Anglo-Dutch Elsevier, part of Reed Elsevier. According to their website, their mission is to
publish trusted, leading-edge Scientific, Technical and Medical (STM) information – pushing the frontiers and fueling a continuous cycle of exploration, discovery and application.
However, Elsevier recently admitted to publishing a set of six fake journals, aimed to promote medical products and drugs by the company Merck, but with the appearance of peer-reviewed, scholarly literature. Clearly, trust is not Elsevier's top priority.What is Elsevier's top priority, though, is making money. Like all scholarly publishers, Elsevier is thriving, despite global financial and economic crises in recent years:
How can a private company be so isolated from the general economy? The reason is that they're largely funded by the tax payer and so far education and R&D budgets have been relatively spared. How do commercial publishers do their job? Here is a brief sketch of how a scholarly paper comes about:
Thus, according to their website, 7,000 paid journal editors are working for the approx. 2,000 journals of Elsevier, while 970,000 unpaid board members, reviewers and authors, largely funded by the tax payer, are donating their time, brains and other valuable resources to the corporation. With hardly any labor costs to speak of and great value provided from outside for free by tax-funded researchers, it is not surprising hat corporate publishers sport great profit margins:
- Researchers generate data
- Researchers write manuscript
- Publisher's editor sends manuscript to other researchers who peer-review the manuscript at no cost to the publisher
- Researchers modify the manuscript
- Researchers pay page charges
- Publisher copy-edits manuscript and puts it online.
- Library or researcher pays subscription fees to access article
| Publisher | Revenue | Profit | Margin |
| Elsevier | £2b | £724m | 36% |
| Springer’s Science + Business Media | €866m | €294m | 33.9% |
| John Wiley & Sons | $253 | $106 | 42% |
| Informa.plc | £145 | £47 | 32.4% |
On top of very small up front costs publishers increase subscription prices manifold beyond inflation:
Quite obviously, with low costs and an ever increasing stream of tax funds burning holes in your pocket, you wonder how all the money could be invested to protect your shareholder value for the future. Therefore, commercial publishers:
Comparing commercial with non-profit publishers shows how competition doesn't bring the price down in scholarly communication: non-profit publishers are providing a publishing service that is consistently half or less of what commercial publishers provide (see also here). Therefore, I am very skeptical of suggestions to transform the scholarly communication ecosystem into a service business. Given that commercial publishers have a proven track record of untrustworthiness, price-gouging and political interference, what would keep them from increasing their prices for the services they provide, just as they have increased subscription prices?
- Buy access to elected representatives
- Use this access to lobby for protective legislation
- Pay full-time employees for government lobbying
- Support SOPA
- Discredit Open Access by hiring professional 'pit-bull' campaigners
- Lobby against Open Access at the US White House
No, the evidence is very clear, we need to rid the scholarly communication system from commercial publishers if we want to reduce or at least limit the burden on tax-payers:
Any proponent of for-profit scholarly publishing first needs to explain why future commercial publishers' behavior should dramatically change from current and past behavior, before any other arguments will even be considered.
- Just eliminating profits will cut publishing costs by approx. US$4b annually
- 1.5 million papers will have to be published anyway, so no jobs will be lost, just transferred
- per-publication costs will come down further as scholarly communication becomes completely online.
Posted on Tuesday 10 January 2012 - 07:07:36 comment: 11
comment: 11| open access publishing elsevier RWA SOPA OSTP corporation |
Apparently, the Open Access movement is falling behind and needs better 'Government Relations'. Today, everyone has their "Vice President for Government Relations" or some other office like that: Universities (e.g., University of Colorado, UM, Rice, the UC system, Cornell, Duke, Harvard, Washington State, University of Minnesota, Columbia, Carnegie Mellon, only to name a few), professors (via AAUP) and of course, the scholarly publishing industry, for example Elsevier's Angelika Lex, "Vice President for Academic and Government Relations".
These kinds of relations to governments are important for the commercial publishers of academic research. Without such relations, their highly profitable business would probably already have collapsed. Or how could one otherwise explain that a business which relies exclusively on tax-funds is thriving with record profits in times like these? Elsevier alone made over US$1b in adjusted operating profits in 2010 (slide 27). After all, they receive our manuscripts for free, then we review it for them for free, after peer-review, we pay their page charges and when our work is published, we pay again for their subscriptions, sometimes tens of thousands of dollars/euros per year per journal. Thus, our largely taxpayer-funded salaries pay for the time we spend researching and writing and submitting and reviewing. Our largely tax-payer funded grants pay for the page charges and our largely taxpayer funded libraries pay for their subscription fees. Given that these publishers add absolutely zero value to our work, besides some bandwidth and storage, one really has to wonder why the tax-payer is still allowing Elsevier' shareholders to pocket a billion every year.
These past few days, we've seen a rare glimpse into how these publishers secure their profits. Not only do they invest in full-time employees whose sole purpose it is to lobby governments into preventing Open Access. They also buy access to elected members of parliaments (see here for some more data). I've wondered yesterday already, if it was coincidence, that the anti-OA bill that was sponsored by the representative that Elsevier donated to, comes just around the same time that the White House OSTP extended their deadline for their RFIs on Open Access to January 12, because only the publishers had provided their perspective until the first deadline. Is the 'Research Works Act' HR3699 a distraction to prevent a massive influence of scientists on the OSTP RFIs? For all the background you might want to get on tis new piece of legislation see this collection of links by John Dupuis.
Clearly, the publishers are doing what they can to stop the tax-payers from realizing how badly they're being milked. Already in 2007 they launched an anti-OS campaign, PRISM, which failed miserably due to a massive backlash from the public.
Compare the language of the proposed RWA legislation:
No Federal agency may adopt, implement, maintain, continue, or otherwise engage in any policy, program, or other activity that:
(1) causes, permits, or authorizes network dissemination of any private-sector research work without the prior consent of the publisher of such work; or
(2) requires that any actual or prospective author, or the employer of such an actual or prospective author, assent to network dissemination of a private-sector research work.
With the language of the answer that the Publisher of the Ecological Society of America for the 'Requests for Information' (RFI) from the White House's Office of Science and Technology Policy (OSTP) on public access to publicly funded research.: (1) causes, permits, or authorizes network dissemination of any private-sector research work without the prior consent of the publisher of such work; or
(2) requires that any actual or prospective author, or the employer of such an actual or prospective author, assent to network dissemination of a private-sector research work.
Government mandates for publishers to make their work available online without compensation will endanger the U.S. scholarly publishing system.
or the statement on the PRISM website: PRISM expresses concerns about the unintended consequences of unfunded government mandates and mandatory one-size-fits-all policies that underestimate the complexities and differing needs of the scientific community and scientific journals. They mean the same Open Access mandates as above
or how Tom Reller, Vice President and Head of Global Corporate Relations of Elsevier supports RWA: But while the government may fund the research, it does not fund the peer review process, editing, or publication of these private-sector information products. Elsevier and other commercial and non-profit publishers invest hundreds of millions of dollars each year in managing the publication of journal articles. Government mandates that require private-sector information products to be made freely available undermine the industry’s ability to recoup these investments.
Needless to say, Elsevier also supports SOPA.Obviously, what the publishing industry is doing is hardly worth calling "investment" if even its supporters claim they only invest a fraction of their operating profits (see above). A few hundred million in "investments" doesn't seem like they'll accomplish a lot for such a large enterprise. It's probably what they mean to express that they must buy new servers every now and then, too.
Given this continuity in their efforts to block Open Access, it is not entirely unrealistic to expect the industry to oppose OA on multiple levels at the same time and wage war by attacking OA in a two-pronged approach on two fronts simultaneously: both by supporting RWA and by providing many industry-friendly answers to the OSTP RFIs. Given the attention RWA has gotten, maybe we will be able to block this legislation, but have enough of OA supporters sent in their answers to the OSTP RFIs? Is the RWA bill also intended as a convenient distraction from the OSTP RFIs? Are we capable of defeating the commercial publishers on two fronts at once?
What can Open Access supporters do?
- Contact the representatives sponsoring the RWA bill, Rep. Darrell Issa (R-CA) and Rep. Carolyn Maloney (D-NY), and tell them that the bill is a bad idea and why.
- Answer the RFIs of the White House OSTP
- Contact the Government Relations Office of your university to do the two above.
Oh, and just in case you think the scholarly publishing industry deserves a break for their continued efforts to somehow wiggle themselves around the fact that they've become obsolete, there's a very fitting passage in "Life-Line", a short story by American author Robert A. Heinlein. Published in 1939 (HT pmr):
There has grown up in the minds of certain groups in this country the notion that because a man or corporation has made a profit out of the public for a number of years, the government and the courts are charged with the duty of guaranteeing such profit in the future, even in the face of changing circumstances and contrary to public interest. This strange doctrine is not supported by statute or common law. Neither individuals nor corporations have any right to come into court and ask that the clock of history be stopped, or turned back.
See also this excellent satire on the matter.Now, it's impossible to know if the following two events are related, but it sure is some strange coincidence. The internet right now is abuzz with talks about a new piece of legislation being introduced in the US, apparently threatening to prevent Open Access to publicly funded research, the Research Works Act, H.R. 3699. There is a ton of information on this proposed bill, from The Atlantic, Michael Eisen, Jonathan Eisen, Tim O'Reilly, John Dupuis or Peter Suber, Boing Boing and many more. People are writing to their representatives to try and prevent this legislation from being signed into law.
And right now the deadline has been extended to answer the 'Requests for Information' (RFI) from the White House's Office of Science and Technology Policy (OSTP) on public access to publicly funded research. With these RFIs, the Obama administration is basically asking for your opinion on Open Access (see also here, here, here and here). There are two sets of questions, one on public access to scholarly literature and one on digital data. There are, of course, two camps on this issue. Publishers (such as ESA) have already answered: they want to kill Open Access (this of course means they endorse the Research Works Act as well). Has anyone else seen other public answers from publishers? It seems they're not so open about this (sorry).
In contrast, the stakeholders on the side of the public support Open Access. Harvard University has already provided their response, Kitware's response on literature and data is on Google Docs and Stevan Harnad has also responded.However, the Research Works Act and now this extension of the RFI deadline can mean only one thing: the publishing industry is working to stop Open Access and this is not the first time. A huge counter-movement stopped this initiative dead from the start in 2007 and we need to do this again right now. A democracy works by the numbers, so now is the time to make sure Washington hears your voice. If you're in the US, contact your representatives and explain to them why the Research Works Act is a bad idea (maybe like this). No matter where you are based, answer the RFIs of the OSTP to let the White House know how important Open Access is to the entire world. They are looking for answers from
“non-Federal stakeholders, including the public, universities, nonprofit and for-profit publishers, libraries, federally funded and non-federally funded research scientists, and other organizations and institutions with a stake in long-term preservation and access to the results of federally funded research,”
The numbers count, so even if you have signed any of the collective responses out there, send an individual email again with your answer. And, ideally, make your answer public, if you can, for others to share and send to the OSTP.Just to offer an additional, shorter list of answers to the ones I linked to above, I've put my own answers below the fold (literature for now, data will follow later).
[ Read the rest ... ]
Posted on Friday 06 January 2012 - 11:29:40 comment: 0
comment: 0| Open Access OSTP RFI publishing policy politics |
In what might become a review article, I've recently been collecting published data about Thomson Reuters' Impact Factor (IF). So far, this data suggests that the IF predicts retractions better than it predicts citations and that this, in part, appears to be due to less reliable research being published in high-IF journals. At the moment, we lack the data to understand more about these relationships, but it may be that what has been termed the 'decline effect' might at least in part be due to journal rank as defined by IF. Journal rank, of course, being vital for a researcher's livelihood: no papers in high-IF journals usually means burger-flipping becoming a lucrative career option for a senior postdoc. The idea behind this way of deciding about the careers of scientists is straightforward: high-IF journals publish high-quality research and if you don't publish high quality research you should be looking for another job.
But not only for scientists is the IF a vital number. Journals survive on subscription fees than can be as high as several tens of thousands of Euros/dollars per year. When deciding which journals to subscribe to, libraries often look at the IF of the journals. The idea being that high-IF journals publish high-quality research and thus should be available for the faculty (as opposed to the low-IF/low-quality journals). Thus, just as scientists might not necessarily submit their 'best' work to high-IF journals, but rather their 'splashiest' manuscripts, i.e., the ones with the most surprising results, journals have an incentive to increase their IF as well: the higher the IF, the higher the number of subscriptions.
The way Thomson Reuters comes up with the IF makes it particularly easy for journals to increase their IF: publishers have the possibility to negotiate how their IF is calculated. In the case of PLoS Medicine, the negotiation range was between 2 and about 11. However, these negotiations take place behind closed doors and so we only rarely become aware of them. A few years ago, triggered by a reference in an article, I went to the Journal Citation Reports (subscription required) website of Thomson Reuters and looked up the IFs of the journal Current Biology in 2002 and 2003, the two IFs following the purchase of Current Biology by Cell Press (owned by Elsevier). You can have a look the screenshots with all the relevant data for 2002 and 2003, but I've zoomed into the relevant parts below:
You can see how Thomson calculates the IF for 2002: number of citations in the current year to papers in the preceding two years, divided by the number of 'citable items' in these years. Because of the IF covering two years, the next IF, that from 2003, overlaps with the previous one in some of the data from 2001. Clearly, the information about what was published should be identical: 528 papers in 2001. Now let's see if this is what we find in the 2003 JCR:
Interestingly, while the number of citations has remained roughly constant from one year to the next, the number of papers published dropped from 528 to only 300. Consequently, Current Biology's IF jumped from 7 to almost 12, supporting the description in the PLoS Medicine editorial about the negotiations taking place between publishers and Thomson Reuters. It is difficult to imagine how sometime in 2002, several hundred published papers somehow got lost in the Thomson Reuters database. Why is it even possible to enter two different values for the same year? It is also difficult to believe that this adjustment happened just coincidentally immediately after Current Biology was bought by the publisher with the deepest pockets, annually netting profits in the hundreds of millions. It is rather telling that Thomson did not even chose to wait for a year to avoid at least the impression of manipulations.
It continues to be an embarrassment for science that we rely on such a blatantly anti-scientific number for our hire-and-fire decisions and it spells trouble for the generation of scientists who are to come of this system. Maybe the 'year of retractions' in 2011 will be the new normal?
Posted on Tuesday 03 January 2012 - 13:17:42 comment: 5
comment: 5| impact factor current biology publishing citations |
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