While there has been a lot of talk about data repositories and data publication there remains a real lack of good tools that are truly attractive to research scientists and also provide a route to more general and effective data sharing. Peter Murray-Rust has recently discussed the deficiencies of the traditional institutional repository as a research data repository in some depth [1, 2, 3, 4].
Data publication approaches and tools are appearing including Dryad, Figshare, BuzzData and more traditional venues such as GigaScience from BioMedCentral but these are all formal mechanisms that involve significant additional work alongside an active decision to “publish the dataâ€. The research repository of choice remains a haphazard file store and the data sharing mechanism of choice remains email. How do we bridge this gap?
One of the problems with many efforts in this space is how they are conceived and sold as the user. “Making it easy to put your data on the web†and “helping others to find your data†solve problems that most researchers don’t think they have. Most researchers don’t want to share at all, preferring to retain as much of an advantage through secrecy as possible. Those who do see a value in sharing are for the most part highly skeptical that the vast majority of research data can be used outside the lab in which it was generated. The small remainder who see a value in wider research data sharing are painfully aware of how much work it is to make that data useful.
A successful data repository system will start by solving a different problem, a problem that all researchers recognize they have, and will then nudge the users into doing the additional work of recording (or allowing the capture of) the metadata that could make that data useful to other researchers. Finally it will quietly encourage them to make the data accessible to other researchers. Both the nudge and the encouragement will arise by offering back to the user immediate benefits in the form of automated processing, derived data products, or other more incentives.
But first the problem to solve. The problem that researchers recognize they have, in many cases prompted by funder data sharing plan requirements, is to properly store and back up their data. A further problem most PIs realize they have is access to the data of their group in a useful form. So they initial sales pitch for a data repository is going to be local and secure backup and sharing within the group. This has to be dead simple and ideally automated.
Such a repository will capture as much data as possible at source as it is generated. Just grabbing the file and storing it with the minimal contextual data, of who (which directory was it saved in), when (aquired from the initial file datestamp), and what (where has it come from), backing it up and exposing it to the research group (or subsets of it) via a simple web service. It will almost certainly involve some form of Dropbox-style system which synchronises a users own data across their own devices. Here is an immediate benefit. I don’t have to get the pen drive out of my pocket if I’m confident my new data will be on my laptop when I get back to it.
It will allow for simple configuration on each instrument that sets up a target directory and registers a filetype so that the system can recognize what instrument, or computational process, a file came from (the what). The who can be more complex, but a combination of designated directories (where a user has their own directory of data on a specific instrument), login info, and where required low irritant requests or claiming systems can be built. The when is easy. The sell here is in two parts, directory synching across computers means less mucking around with USB keys. And the backup makes everyone feel better, the researcher in the lab, the PI, and the funder.
So far so good, and there are in fact examples of systems like this that exist in one form or another or are being developed including DataStage within the DataFlow project from David Shotton’s group at Oxford, the Clarion project (PMR group at Cambridge) and Smart Research Frameworks (that I have an involvement with) led by Jeremy Frey at Southampton. I’m sure there are dozens of other systems or locally developed tools that do similar things and these are a good starting position.
The question is how do you take systems like this and push it to the next level. How do capture, or encourage the user to provide, enough metadata to actually make the stored data more widely useful? Particularly when they don’t have any real interest in sharing or data publication? I think that there is a significant potential in offering downstream processing of the data.
If This Then That (IFTTT) is a startup that has got quite a bit of attention over the past few weeks as it has come into public beta. The concept is very simple. For a defined set of services there are specific triggers (posting a tweet, favouriting a YouTube video) that can be used to set off another action at another service (send an email, bookmark the URL of the tweet or the video). What if we could offer data processing steps to the user? If the processing steps happen automatically but require a bit more metadata will that provide the incentive to get that data in?
This concept may sound a lot like the functionality provided by workflow engines but there is a difference. Workflow systems are generally very difficult for the general user to setup. This is mostly because they solve a general problem, that of putting any object into any suitable process. IFTTT offers something much simpler, a small set of common actions on common objects, that solves the 80/20 problem. Workflows are hard because they can do anything with any object. And that flexibility comes at a price because it is difficult to know whether that csv file is from a UV-Vis instrument, a small-angle x-ray experiment, or a simulated data set.
But locally, within a research group those there is a more limited set of data objects. With a local (or localized) repository it is possible to imagine plugins that do common single steps on common files. And because the configuration is local there is much less metadata required. But in turn that configuration provides metadata. If a particular filetype from a directory is configured for automated calculation of A280 for protein concentrations then we know that those data files are UV-Vis spectra. What is more, once we know that we can offer an automated protein concentration calculator. This will only work if the system knows what protein you are measuring, an incentive to identify the sample when you do the measurement.
The architecture of such a system would be relatively straightforward. A web service provides the cloud based backup and configuration for captured data files and users. Clients that sit on group users’ personal computers as well as on instruments grab their configuration information from the central repository. They might simply monitor specified directories, or they might pop up with a defined set of questions to capture additional metadata. Users register the instruments that they want to “follow†and when a new data file is generated with their name on it, it is also synchronized back to their registered devices.
The web service provides a plugin architecture where appropriate plugins for the group can be added from some sort of marketplace or online. Plugins that process data to generate additional metadata (e.g. by parsing a log file) can add that to the record of the data file. Those that generate new data will need to be configured as to where that data should go and who should have it synchronised. The plugins will also generate a record of what they did, providing an audit and provenance trail. Finally plugins can provide notifcation back to the users via email, the webservice, or a desktop client, of queued processes that need more information to proceed. The user can mute these but equally the encouragement is there to provide a little more info.
Finally the question of sharing and publication. For individual data file sharing sites like Figshare, plugins might enable straightforward direct submission of files submitted into a specific directory. For collections of data, such as those supported by Dryad, there will need to be to group files together but again this could be as simple as creating a directory. Even if files are copied and pasted or removed from their “proper directories†the system stands a reasonable chance of recognizing files it has already seen and inferring their provenance.
By making it easy to share and easier to satisfy data sharing requests by pushing data to a public space (while still retaining some ability to see how it is being used and by who) the substrate that is required to build better plugins, more functionality, and above all better discovery tools will be provided, and in turn those tools will start to develop. As the tools and functionality develop then the value gained by sharing will rise creating a virtuous circle, encouraging both good data management practice, good metadata provision, and good sharing.
This path starts with things we can build today, and in some cases already exist. It becomes more speculative as it goes forward. There are issues with file synching and security. Things will get messy. The plugin architecture is nothing more than hand waving at the moment and success will require a whole ecosystem of repositories and tools for operating on them. But it is a way forward that looks plausible to me. One that solves the problems researchers have today and guides them towards a tomorrow where best practice is a bit closer to common practice.
Science Online London ran late last week and into the weekend and I was very pleased to be asked to run a panel, broadly speaking focused on evaluation and incentives. Now I had thought that the panel went pretty well but I’d be fibbing if I said I wasn’t a bit disappointed. Not disappointed with the panel members or what they said. Yes it was a bit more general than I had hoped and there were things that I wished we’d covered but the substance was good from my perspective. My disappointment was with the response from the audience, really on two slightly different points.
The first was the lack of response to what I thought were some of the most exciting things I’ve heard in a long time from major stakeholders. I’ll come back to that later. But a bigger disappointment was that people didn’t seem to connect the dots to their own needs and experiences.
Science Online, both in London and North Carolina forms, has for me always been a meeting where the conversation proceeds at a more sophisticated level than the usual. So I pitched the plan of the session at where I thought the level should be. Yes we needed to talk about the challenges and surface the usual problems, non-traditional research outputs and online outputs in particular don’t get the kind of credit that papers do, institutions struggle to give credit for work that doesn’t fit in a pigeonhole, funders seem to reward only the conventional and traditional, and people outside the ivory tower struggle to get either recognition or funding. These are known challenges, the question is how to tackle them.
The step beyond this is the hard one. It is easy to say that incentives need to change. But incentives don’t drop from heaven. Incentives are created within communities and they become meaningful when they are linked to the interests of stakeholders with resources. So the discussion wasn’t really about impact, or funding, or to show that nothing can be done by amateurs. The discussion was about the needs of institutions and funders and how they can be served by what is being generated by the online community. It was also about the constraints they face in acting. But fundamentally you had major players on the stage saying “this is the kind of thing we need to get the ball rollingâ€.
Make no mistake, this is tough. Everyone is constrained and resources are tight but at the centre of the discussion were the key pointers to how to cut through the knot. The head of strategy at a major research university stated that universities want to play a more diverse role, want to create more diverse scholarly outputs, and want to engage with the wider community in new ways. That smart institutions will be looking to diversify. The head of evaluation at a major UK funder said that funders really want to know about non-traditional outputs and how they were having a wider impact. That these outputs are amongst the best things they can talk about to government. That they will be crucial to make the case to sustain science funding.
Those statements are amongst the most direct and exciting I have heard in some years of advocacy in this space. The opportunity is there, if you’re willing to put the effort in to communicate and to shape what you are doing to match to match their needs. As Michael Nielsen said in his morning keynote this is a collective action problem. That means finding what unites the needs of those doing with the needs of those with resources. It means compromise, and it means focusing on the achievable, but the point of the discussion was to identify what might be achievable.
So mostly I was disappointed that the excitement I felt wasn’t mirrored in the audience. The discussion about incentives has to move on. Saying that “institutions should do X†or “funders should do Y†gets us nowhere. Understanding what we can do together with funders and institutions and other communities to take the online agenda forward and understanding what the constraints are is where we need to go. The discussion showed that both institutions and funders know that they need what the community of online scientists can do. They don’t know how to go about it, and they don’t even know very much what we are doing, but they want to know. And when they do know they can advise and help and they can bring resources to bear. Maybe not all the resources you would like, and maybe not for all the things you would like, but resources nonetheless.
With a lot of things it is easy to get too immersed in the detail of these issues and to forget that people are looking in from the outside without the same context. I guess the fact that I pulled out what might have seemed to the audience to be just asides as the main message is indicative of that. But I really want to get that message out because I think it  is critical if the community of online scientists wants to be the mainstream. And I think it should be.
The bottom line is that smart funders and smart institutions value what is going on online. They want to support it, they want to be seen to supportit, but they’re not always sure how to go about it and how to judge its quality. But they want to know more. That’s where you come in and that’s why the session was relevant. Lars Fischer had it absolutely right: “I think the biggest and most consequential incentive for scientists is (informal) recognition by peers.†You know, we know, who is doing the good stuff and what is valuable. Take that conversation to the funders and the institutions, explain to them what’s good and why, and tell the story of what the value is. Put it in your CV, demand that promotion panels take account of it, whichever side of the table you are on. Show that you make an impact in language that they understand. They want to know. They may not always be able to act – funding is an issue – but they want to and they need your help. In many ways they need our help more than we need theirs. And if that isn’t an incentive then I don’t know what is.
1. What ethical and legal principles should govern access to research results and data? How can ethics and law assist in simultaneously protecting and promoting both public and private interests?
There are broadly two principles that govern the ethics of access to research results and data. Firstly there is the simple position that publicly funded research should by default be accessible to the public (with certain limited exceptions, see below). Secondly claims that impinge on public policy, health, safety, or the environment, that are based on research should be supported by public access to the data. See more detail in answer to Q2.
2 a) How should principles apply to publicly-funded research conducted in the public interest?
By default research outputs from publicly funded research should be made publicly accessible and re-usable in as timely a manner as possible. In an ideal world the default would be immediate release, however this is not a practically accessible goal in the near future. Cultural barriers and community inertia prevent the exploitation of technological tools that demonstrably have the potential enable research to move faster and more effectively. Research communication mechanisms are currently shackled to the requirements of the research community to monitor career progression and not optimised for effective communication.
In the near term it is practical to move towards an expectation that research outputs that support published research should be accessible and re-usable. Reasonable exceptions to this include data that is personally identifiable, that may place cultural or environmental heritage at risk, that places researchers at risk, or that might affect the integrity of ongoing data collection. The key point is that while there are reasonable exceptions to the principle of public access to public research outputs that these are exceptions and not the general rule.
What is not reasonable is to withhold or limit the re-use of data, materials, or other research outputs from public research for the purpose of personal advancement, including the “squeezing out of a few more papers”. If these outputs can be more effectively exploited elsewhere then this a more efficient use of public resources to further our public research agenda. The community has placed the importance of our own career advancement ahead of the public interest in achieving outcomes from public research for far too long.
What is also politically naive is to believe or even to create the perception that it is acceptable to withhold data on the basis that “the public won’t understand” or “it might be misused”. The web has radically changed the economics of information transfer but it has perhaps more importantly changed the public perception on access to data. The wider community is rightly suspicious of any situation where public information is withheld. This applies equally to publicly funded research as it does to government data.
2 b) How should principles apply to privately-funded research involving data collected about or from individuals and/or organisations (e.g. clinical trials)?
Increasingly public advocacy groups are becoming involved in contributing to a range of research activities including patient advocacy groups supporting clinical trials, environmental advocacy groups supporting data collection, as well as a wider public involvement in, for instance, citizen science projects.
In the case where individuals or organisations are contributing to research they have a right for that contribution to be recognised and a right to participate on their own terms (or to choose not to participate where those terms are unacceptable).
Organised groups (particularly patient groups) are of growing importance to a range of research. Researchers should expect to negotiate with such groups as to the ultimate publication of data. Such groups should have the ability to demand greater public release and to waive rights to privacy. Equally contributors have a right to expect a default right to privacy where personally identifiable information is involved.
Privacy trumps the expectation of data release and the question of what is personally identifiable information is a vexed question which as a society we are working through. Researchers will need to explore these issues with participants and to work to ensure that data generated can be anonymised in a way that enables the released data to effectively support the claims made from it. This is a challenging area which requires significant further technical, policy, and ethics work.
2 c) How should principles apply to research that is entirely privately-funded but with possible public implications?
It is clear that public funded research is a public good. By contrast privately funded research is properly a private good and the decision to release or not release research outputs lies with the funder.
It is worth noting that much of the privately funded research in UK universities is significantly subsidised through the provision of public infrastructure and this should be taken into consideration when defining publicly and privately funded research. Here I consider research that is 100% privately funded.
Where claims are made on the basis of privately funded research (e.g. of environmental impact or the efficacy of health treatments) then such claims SHOULD be fully supported by provision of the underlying evidence and data if they are to be credible. Where such claims are intended to influence public policy such evidence and data MUST be made available. That is, evidence based public policy must be supported by the publication of the full evidence regardless of the source of that evidence. Claims made to influence public policy that are not supported by provision of evidence must be discounted for the purposes of making public policy.
2 d) How should principles apply to research or communication of data that involves the promotion of the public interest but which might have implications from the privacy interests of citizens?
See above: the right to privacy trumps any requirement to release raw data. Nonetheless research should be structured and appropriate consent obtained to ensure that claims made on the basis of the research can be supported by an adequate, publicly accessible, evidence base.
3. What activities are currently under way that could improve the sharing and communication of scientific information?
A wide variety of technical initiatives are underway to enable the wider collection, capture, archival and distribution of research outputs including narrative, data, materials, and other elements of the research process. It is technically possible for us today to immediately publish the entire research record if we so choose. Such an extreme approach is resource intensive, challenging, and probably not ultimately a sensible use of resources. However it is clear that more complete and rapid sharing has the potential to increase the effectiveness and efficiency of research.
The challenges in exploiting these opportunities are fundamentally cultural. The research community is focussed almost entirely on assessment through the extremely narrow lens of publication of extended narratives in high profile peer reviewed journals. This cultural bias must be at least partially reversed before we can realise the opportunities that technology affords us. This involves advocacy work, policy development, the addressing of incentives for researchers and above all the slow and arduous process of returning the research culture to one which takes responsibility for the return on the public investment, including economic, health, social, education, and research returns and one that takes responsibility for effective communication of research outputs.
4. How do/should new media, including the blogosphere, change how scientists conduct and communicate their research?
New media (not really new any more and increasingly part of the mainstream) democratise access to communications and increase the pace of communication. This is not entirely a good thing and en masse the quality of the discourse is not always high. High quality depends on the good will, expertise, and experience of those taking part.There is a vast quantity of high quality, rapid response discourse that occurs around research on the web today even if it occurs in many places. The most effective means of determining whether a recent high profile communication stands up to criticism is to turn to discussion on blogs and news sites, not to wait months for a possible technical criticism to appear in a journal. In many ways this is nothing new, it is return to the traditional approaches of communication seen at the birth of the Royal Society itself of direct and immediate communication between researchers by the most efficient means possible; letters in the 17C and the web today.
Alongside the potential for more effective communication of researchers with each other there is also an enormous potential for more effective engagement with the wider community, not merely through “news and views” pieces but through active conversation, and indeed active contributions from outside the academy. A group of computer consultants are working to contribute their expertise in software development to improving legacy climate science software. This is a real contribution to the research effort. Equally the right question at the right time may come from an unexpected source but lead to new insights. We need to be open to this.
At the same time there is a technical deficiency in the current web and that is the management of the sheer quantity of potential connections that can be made. Our most valuable resource in research is expert attention. This attention may come from inside or outside the academy but it is a resource that needs to be efficiently directed to where it can have the most impact. This will include the necessary development of mechanisms that assist in choosing which potential contacts and information to follow up. These are currently in their infancy. Their development is in any case a necessity to deal with the explosion of traditional information sources.
5. What additional challenges are there in making data usable by scientists in the same field, scientists in other fields, ‘citizen scientists’ and the general public?
Effective sharing of data and indeed most research outputs remains a significant challenge. The problem is two-fold, first of ensuring sufficient contextual information that an expert can understand the potential uses of the research output. Secondly the placing of that contextual information in a narrative that is understandable to the widest possible range of users. These are both significant challenges that are being tackled by a large number of skilled people. Progress is being made but a great deal of work remains in developing the tools, techniques, and processes that will enable the cost effective sharing of research outputs.
A key point however is that in a world where publication is extremely cheap then simply releasing whatever outputs exist in their current form can still have a positive effect. Firstly where the cost of release is effectively zero even if there is only a small chance of those data being discovered and re-used this will still lead to positive outcomes in aggregate. Secondly the presence of this underexploited resource of released, but insufficiently marked up and contextualised, data will drive the development of real systems that will make them more useful.
6 a) What might be the benefits of more widespread sharing of data for the productivity and efficiency of scientific research?
Fundamentally more efficient, more effective, and more publicly engaging research. Less repetition and needless rediscovery of negative results and ideally more effective replication and critiquing of positive results are enabled by more widespread data sharing. As noted above another important outcome is that even suboptimal sharing will help to drive the development of tools that will help to optimise the effective release of data.
6 b) What might be the benefits of more widespread sharing of data for new sorts of science?
The widespread sharing of data has historically always lead to entirely new forms of science. The modern science of crystallography is based largely on the availability of crystal structures, bioinformatics would simply not exist without genbank, the PDB, and other biological databases and the astronomy of today would be unrecognizable to someone whose career ended prior to the availability of the Sloan Digital Sky Survey. Citizen science projects of the type of Galaxy Zoo, Fold-IT and many others are inconceivable without the data to support them. Extrapolating from this evidence provides an exciting view of the possibilities. Indeed one which it would be negligent not to exploit.
6 c) What might be the benefits of more widespread sharing of data for public policy?
Policy making that is supported by more effective evidence is something that appeals to most scientists. Of course public policy making is never that simple. Nonetheless it is hard to see how a more effective and comprehensive evidence base could fail to support better evidence based policy making. Indeed it is to be hoped that a wide evidence base, and the contradictions it will necessarily contain, could lead to a more sophisticated understanding of the scope and critique of evidence sources.
6 d) What might be the benefits of more widespread sharing of data for other social benefits?
The potential for wider public involvement in science is a major potential benefit. As in e) above a deeper understanding of how to treat and parse evidence and data throughout society can only be positive.
6 e) What might be the benefits of more widespread sharing of data for innovation and economic growth?
Every study of the release of government data has shown that it leads to a nett economic benefit. This is true even when such data has traditionally been charged for. The national economy benefits to a much greater extent than any potential loss of revenue. While this is not necessarily sufficient incentive for private investors to release data in this case of public investment the object is to maximise national ROI. Therefore release in a fully open form is the rational economic approach.
The costs of lack of acces to publicly funded research outputs by SMEs is well established. Improved access will remove the barriers that currently stifle innovation and economic growth.
6 f) What might be the benefits of more widespread sharing of data for public trust in the processes of science?
There is both a negative and a positive side to this question. On the positive greater transparency, more potential for direct involvement, and a greater understanding of the process by which research proceeds will lead to greater public confidence. On the negative, doing nothing is simply not an option. Recent events have shown not so much that the public has lost confidence in science and scientists but that there is deep shock at the lack of transparency and the lack of availability of data.
If the research community does not wish to be perceived in the same way as MPs and other recent targets of public derision then we need to move rapidly to improve the degree of transparency and accessibility of the outputs of public research.
7. How should concerns about privacy, security and intellectual property be balanced against the proposed benefits of openness?
There is little evidence that the protection of IP supports a nett increase on the return on the public investment in research. While there may be cases where it is locally optimal to pursue IP protection to exploit research outputs and maximise ROI this is not generally the case. The presumption that everything should be patented is both draining resources and stifling British research. There should always be an avenue for taking this route to exploitation but there should be a presumption of open communication of research outputs and the need for IP protection should be justified on a case by case basis. It should be unacceptable for the pursuit of IP protection to damage the communication and downstream exploitation of research.
Privacy issues and concerns around the personal security of researchers have been discussed above. National security issues will in many cases fall under a justifiable exception to the presumption of openness although it is clear that this needs care and probably oversight to retain public confidence.
8. What should be expected and/or required of scientists (in companies, universities or elsewhere), research funders, regulators, scientific publishers, research institutions, international organisations and other bodies?
British research could benefit from a statement of values, something that has the cultural significance of the Haldane principle (although perhaps better understood) or the Hippocratic oath. A shared cultural statement that captures a commitment to efficiently discharging the public trust invested in us, to open processes as a default, and to specific approaches where appropriate would act as a strong centre around which policy and tools could be developed. Leadership is crucial here in setting values and embedding these within our culture. Organisations such as the Royal Society have an important role to play.
Researchers and the research community need to take these responsibilities on ourselves in a serious and considered manner. Funders and regulators need to provide a policy framework, and where appropriate community sanctions for transgression of important principles. Research institutions are for the most part tied into current incentive systems that are tightly coupled to funding arrangements and have limited freedom of movement. Nonetheless a serious consideration of the ROI of technology transfer arrangements and of how non-traditional outputs, including data, contribute to the work of the institution and its standing are required. In the current economic climate successful institutions will diversify in their approach. Those that do not are unlikely to survive in their current form.
Other comments
This is not the first time that the research community has faced this issue. Indeed it is not even the first time the Royal Society has played a central role. Several hundred years ago it was a challenge to persuade researchers to share information at all. Results were hidden. Sharing was partial, only within tight circles, and usually limited in scope. The precursors of the Royal Society played a key role in persuading the community that effective sharing of their research outputs would improve research. Many of the same concerns were raised; concerns about the misuse of those outputs, concerns about others stealing ideas, concerns about personal prestige and the embarrassment potential of getting things wrong.
The development of journals and the development of a values system that demanded that results be made public took time, it took leadership, and with the technology of the day the best possible system was developed over an extended period. With a new technology now available we face the same issues and challenges. It is to be hoped that we tackle those challenges and opportunities with the same sense of purpose.
I developed an interest in research evaluation as an advocate of open research process. It is clear that researchers are not going to change themselves so someone is going to have to change them and it is funders who wield the biggest stick. The only question, I thought, Â was how to persuade them to use it
Of course it’s not that simple. It turns out that funders are highly constrained as well. They can lead from the front but not too far out in front if they want to retain the confidence of their community. And the actual decision making processes remain dominated by senior researchers. Successful senior researchers with little interest in rocking the boat too much.
The thing you realize as you dig deeper into this as that the key lies in finding motivations that work across the interests of different stakeholders. The challenge lies in finding the shared objectives. What it is that unites both researchers and funders, as well as government and the wider community. So what can we find that is shared?
I’d like to suggest that one answer to that is Impact. The research community as a whole has stake in convincing government that research funding is well invested. Government also has a stake in understanding how to maximize the return on its investment. Researchers do want to make a difference, even if that difference is a long way off. You need a scattergun approach to get the big results, but that means supporting a diverse range of research in the knowledge that some of it will go nowhere but some of it will pay off.
Impact has a bad name but if we step aside from the gut reactions and look at what we actually want out of research then we start to see a need to raise some challenging questions. What is research for? What is its role in our society really? What outcomes would we like to see from it, and over what timeframes? What would we want to evaluate those outcomes against? Economic impact yes, as well as social, health, policy, and environmental impact. This is called the ‘triple bottom line’ in Australia. But alongside these there is also research impact.
All these have something in common. Re-use. What we mean by impact is re-use. Re-use in industry, re-use in public health and education, re-use in policy development and enactment, and re-use in research.
And this frame brings some interesting possibilities. We can measure some types of re-use. Citation, retweets, re-use of data or materials, or methods or software. We can think about gathering evidence of other types of re-use, and of improving the systems that acknowledge re-use. If we can expand the culture of citation and linking to new objects and new forms of re-use, particularly for objects on the web, where there is some good low hanging fruit, then we can gather a much stronger and more comprehensive evidence base to support all sorts of decision making.
There are also problems and challenges. The same ones that any social metrics bring. Concentration and community effects, the Matthew effect of the rich getting richer. We need to understand these feedback effects much better and I am very glad there are significant projects addressing this.
But there is also something more compelling for me in this view. It let’s us reframe the debate around basic research. The argument goes we need basic research to support future breakthroughs. We know neither what we will need nor where it will come from. But we know that its very hard to predict – that’s why we support curiosity driven research as an important part of the portfolio of projects. Yet the dissemination of this investment in the future is amongst the weakest in our research portfolio. At best a few papers are released then hidden in journals that most of the world has no access to and in many cases without the data, or other products either being indexed or even made available. And this lack of effective dissemination is often because the work is perceived as low, or perhaps better, slow impact.
We may not be able to demonstrate or to measure significant re-use of the outputs of this research for many years. But what we can do is focus on optimizing the capacity, the potential, for future exploitation. Where we can’t demonstrate re-use and impact we should demand that researchers demonstrate that they have optimized their outputs to enable future re-use and impact.
And this brings me full circle. My belief is that the way to ensure the best opportunities for downstream re-use, over all timeframes, is that the research outputs are open, in the Budapest Declaration sense. But we don’t have to take my word for it, we can gather evidence. Making everything naively open will not always be the best answer, but we need to understand where that is and how best to deal with it. We need to gather evidence of re-use over time to understand how to optimize our outputs to maximize their impact.
But if we choose to value re-use, to value the downstream impact that our research or have, or could have, then we can make this debate not about politics or ideology but how about how best to take the public investment in research and to invest it for the outcomes that we need as a society.
Quite some months ago an article in Cancer Therapy and Biology by Scott Kern of Johns Hopkins kicked up an almighty online stink. The article entitled “Where’s the passion” bemoaned the lack of hard core dedication amongst the younger researchers that the author saw around him…starting with:
It is Sunday afternoon on a sunny, spring day.
I’m walking the halls—all of them—in a modern $59 million building dedicated to cancer research. A half hour ago, I completed a stroll through another, identical building. You see, I’m doing a survey. And the two buildings are largely empty.
The point being that if they really cared, those young researchers would be there day in-day out working their hearts out to get to the key finding. At one level this is risible, expecting everyone to work 24×7 is not a good or efficient way to get results. Furthermore you have to wonder why these younger researchers have “lost their passion”. Why doesn’t the environment create that naturally, what messages are the tenured staff sending through their actions. But I’d be being dishonest if there wasn’t a twinge of sympathy for me as well. Anyone who’s run a group has had that thought that the back of their mind; “if only they’d work harder/smarter/longer we’d be that much further ahead…”.
But all of that has been covered by others. What jumped out of the piece for me at the time were some other passages, ones that really got me angry.
When the mothers of the Mothers March collected dimes, they KNEW that teams, at that minute, were performing difficult, even dangerous, research in the supported labs. Modern cancer advocates walk for a cure down the city streets on Saturday mornings across the land. They can comfortably know that, uh…let’s see here…, some of their donations might receive similar passion. Anyway, the effort should be up to full force by 10 a.m. or so the following Monday.
[…]
During the survey period, off-site laypersons offer comments on my observations. “Don’t the people with families have a right to a career in cancer research also?†I choose not to answer. How would I? Do the patients have a duty to provide this “rightâ€, perhaps by entering suspended animation?
Now these are all worthy statements. We’d all like to see faster development of cures and I’ve no doubt that the people out there pounding the streets are driven to do all they can to see those cures advance. But is the real problem here whether the postdocs are here on a Sunday afternoon or are there things we could do to advance this? Maybe there are other parts of the research enterprise that could be made more efficient…like I don’t know making the results of research widely available and ensuring that others are in the best position possible to build on their results?
It would be easy to pick on Kern’s record on publishing open access papers. Has he made all the efforts that would enable patients and doctors to make the best decisions they can on the basis of his research? His lab generates cell lines that can support further research. Are those freely available for others to use and build on? But to pick on Kern personally is to completely miss the point.
No, the problem is that this is systemic. Researchers across the board seem to have no interest whatsoever in looking closely at how we might deliver outcomes faster. No-one is prepared to think about how the system could be improved so as to deliver more because everyone is too focussed on climbing up the greasy pole; writing the next big paper and landing the next big grant. What is worse is that it is precisely in those areas where there is most public effort to raise money, where there is a desperate need, that attitudes towards making research outputs available are at their worse.
What made me absolutely incandescent about this piece was a small piece of data that some of use have known about for a while but has only just been published. Heather Piwowar, who has done a lot of work on how and where people share, took a close look at the sharing of microarray data. What kind of things are correlated with data sharing. The paper bears close reading (Full disclosure: I was the academic editor for PLoS ONE on this paper) but one thing has stood out from me as shocking since the first time I heard Heather discuss it: microarray data linked to studies of cancer is systematically less shared.
This is not an isolated case. Across the board there are serious questions to be asked about why it seems so difficult to get the data from studies that relate to cancer. I don’t want to speculate on the reasons because whatever they are, they are unnacceptable. I know I’ve recommended this video of Josh Sommer speaking many times before, but watch it again. Then read Heather’s paper. And then decide what you think we need to do about it. Because this can not go on.
Peter Murray-Rust has sparked off another round in the discussion of the value that publishers bring to the scholarly communication game and told a particular story of woe and pain inflicted by the incumbent publishers. On the day he posted that I had my own experience of just how inefficient and ineffective our communication systems are by wasting the better part of the day trying to find some information. I thought it might be fun to encourage people to post their own stories of problems and frustrations with access to the literature and the downstream issues that creates, so here is mine.
I am by no means a skilled organic chemist but I’ve done a bit of synthesis in my time and I certainly know enough to be able to read synthetic chemistry papers and decide whether a particular synthesis is accessible. So on this particular day I was interested in deciding whether it was easy or difficult to make deuterated mono-olein. This molecule can be made by connecting glycerol to oleic acid. Glycerol is cheap and I should have in my hands some deuterated oleic acid in the next month or so. The chemistry for connecting acids to alcohols is straightforward, I’ve even done it myself, but this is a slightly special case. Firstly the standard methods tend to be wasteful of the acid, which in my case is the expensive bit. The second issue is that glycerol has three alcohol groups. I only want to modify one, leaving the other two unchanged, so it is important to find a method that gives me mostly what I want and only a little of what I don’t.
So the question for me is: is there a high yielding reaction that will give me mostly what I want, while wasting as little as possible of the oleic acid? And if there is a good technique is it accessible given the equipment I have in the lab? Simple question, quick trip to Google Scholar, to find reams of likely looking papers, not one of which I had full text access to. The abstracts are nearly useless in this case because I need to know details of yields and methodology so I had several hundred papers, and no means of figuring out which might be worth an inter-library loan. I spent hours trying to parse the abstracts to figure out which were the most promising and in the end I broke…I asked someone to email me a couple of pdfs because I knew they had access. Bear in mind what I wanted to do was spend a quick 30 minutes or so to decide whether this was pursuing in detail. What is took was about three hours, which at full economic cost of my time comes to about £250. That’s about £200 of UK taxpayers money down the toilet because, on the site of the UKs premiere physical and biological research facilities I don’t have access to those papers. Yes I could have asked someone else to look but that would have taken up their time.
But you know what’s really infuriating. I shouldn’t even have been looking at the papers at all when I’m doing my initial search. What I should have been able to do was ask the question:
Show me all syntheses of mono-olein ranked first by purity of the product and secondly by the yield with respect to oleic acid.
There should be a database where I can get this information. In fact there is. But we can’t afford access to the ACS’ information services here. These are incredibly expensive because it used to be necessary for this information to be culled from papers by hand. But today that’s not necessary. It could be done cheaply and rapidly. In fact I’ve seen it done cheaply and rapidly by tools developed in Peter’s group that get around ~95% accuracy and ~80% recall over synthetic organic chemistry. Those are hit rates that would have solved my problem easily and effectively.
Unfortunately despite the fact those tools exist, despite the fact that they could be deployed easily and cheaply, and that they could save researchers vast amounts of time research is being held back by a lack of access to the literature, and where there is access by contracts that prevent us collating, aggregating, and analysing our own work. The public pays for the research to be done, the public pays for researchers to be able to read it, and in most cases the public has to pay again if they should want to read it. But what is most infuriating is the way the public pays yet again when I and a million other scientists waste our time, the public’s time, because the tools that exist and work cannot be deployed.
How many researchers in the UK or world wide are losing hours or even days every week because of these inefficiencies. How many new tools or techniques are never developed because they can’t legally be deployed? And how many hundreds of millions of dollars of public money does that add up to?
”The Howard Hughes Medical Institute, the Max Planck Society and the Wellcome Trust announced today that they are to support a new, top-tier, open access journal for biomedical and life sciences research. The three organisations aim to establish a new journal that will attract and define the very best research publications from across these fields. All research published in the journal will make highly significant contributions that will extend the boundaries of scientific knowledge.” [Press Release]
It has been clear for some time that the slowness of the adoption of open access publication models by researchers is in large part down to terror that we have of stepping out of line and publishing in the ‘wrong’ journals. More radical approaches to publication will clearly lag even further behind while this inherent conservatism is dominant. Publishers like PLoS and BMC have tackled this head on by aiming to create prestigous journals but the top of the pile has remained the traditional clutch of Nature, Science, and Cell.
The incumbent publishers have simultaneously been able to sit back due to a lack of apparent demand from researchers. As the demand from funders has increased they have held back, complaining the business models to support Open Access publication are not clear. I’ve always found the ‘business model’ argument slightly specious. Sustainability is important but scholarly publishing has never really had a viable business model, it has had a subsidy from funders. Part of the problem has been the multiple layers and channels that subsidy has gone through but essentially funders, through indirect funding of academic libraries, have been footing the bill.
Some funders, and the Wellcome Trust has lead on this, have demanded that their researchers make their outputs accessible while simultaneously requiring publishers comply with their requirements on access and re-use rights. But progress has been slow, particularly in opening up what is perceived as the top of the market. Despite major inroads made by PLoS Biology and PLos Medicine those journals perceived as the most prestigious have remain resolutely closed.
Government funders are mostly constrained in their freedom to act but the Wellcome Trust, HHMI, and Max Planck Society have the independence to take the logical step. They are already paying for publication, why not actively support the formation of a new journal, properly open access, and at the same time lend the prestige that their names can bring?
This will send a very strong message, both to researchers and publishers, about what these funders value, and where they see value for money. It is difficult to imagine this will not lead to a seismic shift in the publishing landscape, at least from a political and financial perspective. I don’t believe this journal will be as technically radical as I would like, but it is unlikely it could be while achieving the aims that it has. I do hope the platform it is built on enables innovation both in terms of what is published and the process by which it is selected.
But in a sense that doesn’t matter. This venture can remain incredibly conservative and still have a huge impact on taking the research communication space forward. What it means is that three of the worlds key funders have made an unequivocal statement that they want to see Open Access, full open access on publication without restrictions on commercial use, or text-mining, or re-use in any form, across the whole of the publication spectrum. And if they don’t get it from the incumbent publishers they’re prepared to make it happen themselves.
Full Disclosure: I was present at a meeting at Janelia Farm in 2010 where the proposal to form a journal was discussed by members of the Wellcome, HHMI, and MPG communities.
As a wooly headed social liberal with a strong belief in the power of the internet to connect people it is probably natural for to me have some sympathy for the ideas behind the “Big Society†espoused by the UK Prime Minister. The concept here is that many of the support roles traditionally taken by or at least mediated by government can be more effectively and efficiently provided in the community by direct interactions between members of the public. The potential of the web to inform, support critical debate, and above all connect people is enormous. There is a real potential to create markets for exchange of resources, primarily time and money, between those who have and those who need, while naturally tailoring these services to what is really needed at a local level. The efficiency of markets can be combined with a socialist vision of community responsibility combining the best of both political visions and jettisoning the failures of each.
There is of course trouble in utopia. What actually happens as government withdraws as the guarantor or service provision and hands over the reins to local community groups is a mixture of triumph and farce. A few communities are strong enough to engage their members and deliver services competently and effectively but these are usually the wealthy areas that are already well served. More widely a mixture of incompetence (in a purely technical sense) and a simple lack of people prepared or able to carry this load leads to those areas with poor service provision to receive less. There are groups that will step in to take up the slack but they tend to fall into two groups, either wealthy benefactors or groups with a specific agendas, sometimes with extreme viewpoints. Regardless of motivation, these groups come into communities from the outside. In that sense they are just like government, only with less regulation, probably less experience of service provision, and above all, not part of the community.
Building the technical infrastructure to support the Big Society is easy. But just because technical infrastructure is there doesn’t mean that community members have the time, the resources, or most importantly the motivation to use it. The cultural infrastructure, the assumptions that would motivate people to get involved, the support for people to take time off work (or work shorter hours) so as to spend time in the community, and the trust in systems for pooling the necessary resources simply doesn’t exist. This cultural infrastructure will take a generation to build and will require a focused effort from government, communities, and industry. And it will require money.
So what does this have to do with peer review? Researchers contribute to traditional peer review because it something we expect to do. It is often claimed that we do peer review because we expect the favour of high quality review back in return. I just don’t buy it. If this were true we’d find it much easier to get people to share data (because they’d get data shared back in the future) or materials (similarly). None of this happens because we don’t have a cultural infrastructure that supports and values these behaviours. We do however have an existing cultural infrastructure which supports the need for traditional peer review to be done.
Naturally it follows that those things that aren’t seen as an assumed part of the job don’t get done. Post-publication peer review, despite its potential is one of these things. Data and process sharing are others. Data sharing plans and funder mandates are really just scaffolding. They support the structure that we can see that we want but they aren’t the foundations and pillars that will support a robust community. The moral debate on these issues has fundamentally been won, it is merely a question of implementation and managing the transition. But we now need to look beyond the technical problems and the application of big sticks to understand how we can build the cultural infrastructure that supports a world where reproducibility, effective communication of all research outputs, and ongoing critique of the outputs of others are assumed to be part of the job.
On Monday 30 May I gave evidence at a European Commission hearing on Access to Scientific Information. This is the text that I spoke from. Just to re-inforce my usual disclaimer I was not speaking on behalf of my employer but as an independent researcher.
We live in a world where there is more information available at the tips of our fingers than even existed 10 or 20 years ago. Much of what we use to evaluate research today was built in a world where the underlying data was difficult and expensive to collect. Companies were built, massive data sets collected and curated and our whole edifice of reputation building and assessment grew up based on what was available. As the systems became more sophisticated new measures became incorporated but the fundamental basis of our systems weren’t questioned. Somewhere along the line we forgot that we had never actually been measuring what mattered, just what we could.
Today we can track, measure, and aggregate much more, and much more detailed information. It’s not just that we can ask how much a dataset is being downloaded but that we can ask who is downloading it, academics or school children, and more, we can ask who was the person who wrote the blog post or posted it to Facebook that led to that spike in downloads.
This is technically feasible today. And make no mistake it will happen. And this provides enormous potential benefits. But in my view it should also give us pause. It gives us a real opportunity to ask why it is that we are measuring these things. The richness of the answers available to us means we should spend some time working out what the right questions are.
There are many reasons for evaluating research and researchers. I want to touch on just three. The first is researchers evaluating themselves against their peers. While this is informed by data it will always be highly subjective and vary discipline by discipline. It is worthy of study but not I think something that is subject to policy interventions.
The second area is in attempting to make objective decisions about the distribution of research resources. This is clearly a contentious issue. Formulaic approaches can be made more transparent and less easy to legal attack but are relatively easy to game. A deeper challenge is that by their nature all metrics are backwards looking. They can only report on things that have happened. Indicators are generally lagging (true of most of the measures in wide current use) but what we need are leading indicators. It is likely that human opinion will continue to beat naive metrics in this area for some time.
Finally there is the question of using evidence to design the optimal architecture for the whole research enterprise. Evidence based policy making in research policy has historically been sadly lacking. We have an opportunity to change that through building a strong, transparent, and useful evidence base but only if we simultaneously work to understand the social context of that evidence. How does collecting information change researcher behavior? How are these measures gamed? What outcomes are important? How does all of this differ cross national and disciplinary boundaries, or amongst age groups?
It is my belief, shared with many that will speak today, that open approaches will lead to faster, more efficient, and more cost effective research. Other groups and organizations have concerns around business models, quality assurance, and sustainability of these newer approaches. We don’t need to argue about this in a vacuum. We can collect evidence, debate what the most important measures are, and come to an informed and nuanced inclusion based on real data and real understanding.
To do this we need to take action in a number areas:
1. We need data on evaluation and we need to able to share it.
Research organizations must be encouraged to maintain records of the downstream usage of their published artifacts. Where there is a mandate for data availability this should include mandated public access to data on usage.
The commission and national funders should clearly articulate that that provision of usage data is a key service for publishers of articles, data, and software to provide, and that where a direct payment is made for publication provision for such data should be included. Such data must be technically and legally reusable.
The commission and national funders should support work towards standardizing vocabularies and formats for this data as well critiquing it’s quality and usefulness. This work will necessarily be diverse with disciplinary, national, and object type differences but there is value in coordinating actions. At a recent workshop where funders, service providers, developers and researchers convened we made significant progress towards agreeing routes towards standardization of the vocabularies to describe research outputs.
2. We need to integrate our systems of recognition and attribution into the way the web works through identifying research objects and linking them together in standard ways.
The effectiveness of the web lies in its framework of addressable items connected by links. Researchers have a strong culture of making links and recognizing contributions through attribution and citation of scholarly articles and books but this has only recently being surfaced in a way that consumer web tools can view and use. And practice is patchy and inconsistent for new forms of scholarly output such as data, software and online writing.
The commission should support efforts to open up scholarly bibliography to the mechanics of the web through policy and technical actions. The recent Hargreaves report explicitly notes limitations on text mining and information retrieval as an area where the EU should act to modernize copyright law.
The commission should act to support efforts to develop and gain wide community support for unique identifiers for research outputs, and for researchers. Again these efforts are diverse and it will be community adoption which determines their usefulness but coordination and communication actions will be useful here. Where there is critical mass, such as may be the case for ORCID and DataCite, this crucial cultural infrastructure should merit direct support.
Similarly the commission should support actions to develop standardized expressions of links, through developing citation and linking standards for scholarly material. Again the work of DataCite, CoData, Dryad and other initiatives as well as technical standards development is crucial here.
3. Finally we must closely study the context in which our data collection and indicator assessment develops. Social systems cannot be measured without perturbing them and we can do no good with data or evidence if we do not understand and respect both the systems being measured and the effects of implementing any policy decision.
We need to understand the measures we might develop, what forms of evaluation they are useful for and how change can be effected where appropriate. This will require significant work as well as an appreciation of the close coupling of the whole system.
We have a generational opportunity to make our research infrastructure better through effective evaluation and evidence based policy making and architecture development. But we will squander this opportunity if we either take a utopian view of what might technically feasible, or fail to act for a fear of a dystopian future. The way to approach this is through a careful, timely, transparent and thoughtful approach to understanding ourselves and the system we work within.
The commission should act to ensure that current nascent efforts work efficiently towards delivering the technical, cultural, and legal infrastructure that will support an informed debate through a combination of communication, coordination, and policy actions.
Michael Nielsen is a good friend as well as being an inspiration to many of us in the Open Science community. I’ve been privileged to watch and in a small way to contribute to the development of his arguments over the years and I found the distillation of these years of effort into the talk that he recently gave at TEDxWaterloo entirely successful. Here is a widely accesible and entertaining talk that really pins down the arguments, the history, the successes and the failures of recent efforts to open up science practice.
Professional scientific credit is the central issue
I’ve been involved in many discussions around why the potential of opening up research practice hasn’t lead to wider adoption of these approaches. The answer is simple, and as Michael says very clearly in the opening section of the talk, the problem is that innovative approaches to doing science are not going to be adopted while those that use them don’t get conventional scientific credit. I therefore have to admit to being somewhat nonplussed by GrrlScientist’s assessment of the talk that “Dr Nielsen has missed — he certainly has not emphasised — the most obvious reason why the Open Science movement will not work: credit.”
For me, the entire talk is about credit. He frames the discussion of why the Qwiki wasn’t a huge success, compared to the Polymath project, in terms of the production of conventional papers, he discusses the transition from Galileo’s anagrams to the development of the scientific journal in terms of ensuring priority and credit. Finally he explicitly asks the non-scientist members of the audience to do something that even more closely speaks to the issue of credit, to ask their scientist friends and family what they are doing to make their results more widely available. Remember this talk is aimed at a wider audience, the TEDxWaterloo attendees and the larger audience for the video online (nearly 6,000 when I wrote this post). What happens when taxpayers start asking their friends, their family, and their legislative representatives how scientific results are being made available? You’d better believe that this has an affect on the credit economy.
Do we just need the celebrities to back us?
Grrl suggests that the answer to pushing the agenda forward is to enlist Nobelists to drive projects in the same way that Tim Gowers pushed the Polymath project. While I can see the logic and there is certainly value in moral support from successful scientists we already have a lot of this. Sulston, Varmus, Michael and Jon Eisen, and indeed Michael himself just to name a few are already pushing this agenda. But moral support and single projects are not enough. What we need to do is hack the underlying credit economy, provide proper citations for data and software, exploit the obsession with impact factors.
The key to success in my view is a pincer movement. First, showing that more (if not always completely) open approaches can outcompete closed approaches on traditional assessment measures, something demonstrated successfully by Galaxy Zoo, the Alzeimers Disease Neuroimaging Initiative, and the Polymath Projects. Secondly changing assessment policy and culture itself, both explicitly by changing the measures by which researchers are ranked, and implicitly by raising the public expectation that research should be open.
The pendulum is swinging and we’re pushing it just about every which-way we can
I guess what really gets my back up is that Grrl sets off with the statement that “Open Science will never work” but then does on to put her finger on exactly the point where we can push to make it work. Professional and public credit is absolutely at the centre of the challenge. Michael’s talk is part of a concerted, even quite carefully coordinated, campaign to tackle this issue at a wide range of levels. Michael’s tour of his talk, funded by the Open Society Institute seeks to raise awareness. My recent focus on researchassessment (and a project also funded by OSI) is tackling the same problem from another angle. It is not entirely a coincidence that I’m writing this in a hotel room in Washington DC and it is not at all accidental that I’m very interested in progress towards widely accepted researcher identifiers. The development of Open Research Computation is a deliberate attempt to build a journal that exploits the nature of journal rankings to make software development more highly valued.Â
All of these are part of a push to hack, reconfigure, and re-assess the outputs and outcomes that researchers get credit for and the the outputs and outcomes that are valued by tenure committees and grant panels. And from where I stand we’re making enough progress that Grrl’s argument seems a bit tired and outdated. I’m seeing enough examples of people getting credit and reward for being open and simply doing and enabling better science as a result that I’m confident the pendulum is shifting. Would I advise a young scientist that being open will lead to certain glory? No, it’s far from certain, but you need to distinguish yourself from the crowd one way or another and this is one way to do it. It’s still high risk but show me something in a research career that is low risk and I’ll show something that isn’t worth doing.
What can you do?
If you believe that a move towards more open research practice is a good thing then what can you do to make this happen? Well follow what Michael says, give credit to those who share, explicitly acknowledge the support and ideas you get from others. Ask researchers how they go about ensuring that their research is widely available and above all used. The thing is, in the end changing the credit economy itself isn’t enough, we actually have to change the culture that underlies that economy. This is hard but it is done by embedding the issues and assumptions in the everyday discourse about research. “How useable are your research outputs really?” is the question that gets to the heart of the problem. “How easily can people access, re-use, and improve on your research? And how open are you to getting the benefit of other people’s contribution?” are the questions that I hope will become embedded in the assumptions around how we do research. You can make that happen by asking them.
