Tag: open research

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Who’s in the Club? New frames for understanding knowledge sharing

English: Venn diagram (coloured)
Venn diagram (Photo credit: Wikipedia)

The following is a version of the text I spoke from at the STEPS 2015 Conference, Resource Politics, at a session on Open Science organised by Valleria Arza, where I spoke along with Ross Mounce and Cindy Regalado. This version is modified slightly in response to comments from the audience.

There aren’t too many privileged categories I don’t fall into. White, male, middle class, middle aged, home owner. Perhaps the only claim I could make in the UK context is not having a connection with Oxbridge. The only language I speak is English and I’ve never lived in a non-english speaking country, never lived outside of Australia or England in fact. What do I have to say about developing countries? Or transitional, or emerging or peripheral…all problematic terms rooted in a developed world, western, narrative.

I hope it is more than just a hand-wringing liberal response. I suspect all of us do, genuinely base our work on a conviction that we can make a difference for good. In this context we collectively  believe that the critical tradition of scholarship developed in Western Europe can bring benefits to disadvantaged groups. And after all the resources to actually take action are in our hands or within our gift to influence. Something must be done. We can do something. Therefore we must do it.

Obviously this is an old critique and one that has shaped  decisions about how to act. We seek to move beyond charity and paternalistic intervention to offering frameworks and taking consultative approaches. To requiring a deeper understanding of context. In my own work I’ve tried to focus on offering ideas about processes and implementation, not on what should be done. But my ideas are of course still trapped within the frameworks I work within.

Central to those frameworks for me is “Open”. I’m not going to seek to explain in detail what I mean by “open”. Nor am I going to provide a critical analysis of the issues it raises in a development context, or its dependence on western liberal democratic, or neoliberal, or even libertarian values. Others are better placed to do that. What I do want to propose is that “Open” in the sense that I mean it is a culture, and it is a culture deeply rooted in its particular (north) western historical context.

If you accept that Open is a culture then our traditional thinking would be that it is the product of a particular community. Or rather communities. Again the history is complex but we can identify a complex of groups, clubs if you like, that have grown up with their own motivations and agendas but have sufficient alignment that we can collect them together under the label of “Open”. “Open Source”, “Open Data”, “Open Access”, “Open Science”, but also perhaps “Open Government”, transparency and others. Often these groups are identified with a charismatic individual.

John Hartley and Jason Potts in their book Cultural Science, propose a shift in our usual way of thinking about these groups and their cultures, that is both subtle and to my mind radical. We would usually think of individuals coming together to form groups in a common interest (often framed as an political-economic analysis of the way the collective resources of the group combine to achieve action). The individuals in the group and their values combine to define the culture of the group.

Hartley and Potts invert this. Their claim is that it is culture that creates groups. This inversion, whether you take it at face value as a real description of causation, or simply as a useful way to reframe the analysis has an important consequence. It focuses the unit of analysis onto the group rather than the individual. Rather than asking how individual behaviour lead to the consequences of groups interacting, we ask how cultures do or do not align, reinforce or cancel out.

In the session at the Resource Politics Conference on Tuesday on Assessment of Assessments we heard how governance reflects the structural moves allowed within an institution and how the framing of a problem reflects (or creates) these structures. Martin Mahony spoke of certain framings as “colonising spaces” which I would in turn appropriate as an example of how adaptive cultural elements can be spread through their re-creation or co-creation by groups.

In any case take your pick. New model of how culture, groups, society and sociotechnical institutions  that they co-create actually work and evolve, or a different framing that lets us tackle interesting problems from a new perspective. Either way, is it helpful? And what does it have to do with “development” or “sustainability” or “open” for that matter?

I think its useful (and relevant) because it lets us take a new view on the status of knowledge created in different contexts and it provokes some new ways of asking what we should do with the resources that we have.

First it gives us a license to say that some forms of knowledge are simply incompatible, growing as they do out of different cultures. But crucially it requires us to accept that in both directions – forms of knowledge from other cultures that are inaccessible to us, but also that our knowledge is accessible to others. It also suggests that some forms of compatibility may be defined through absence, exclusion or antagonism.

An anecdote: A few years ago I was working on a program focussing on Scholarly Communication in Sub-Saharan Africa. One striking finding was the way the communities of scholars, in disciplines that traditionally don’t communicate across groups, were actively engaging on social media platforms. Researchers from Russia, Iran, Iraq, Pakistan, India, Madagascar, Zimbabwe, Brazil, and Chile were all discussing the details of the problems they were facing in synthetic chemistry, a discipline that in my world is almost legendary for its obsessive individualism and lack of sharing. They shared the language of chemistry, and of English as the lingua franca, but they shared that with the absent centre of this geographical circle. Their shared culture was one of exclusion from the North Western centre of their discipline.

And yet, our culture, that of western scholarship was still dominant. I was struck yesterday in the “Assessment of Assessment” session focussing as it did on questions of transparency, engagement, and above all framing, that the framing of the session itself was not interrogated. Why, in an area focussed on building an inclusive consensus, is the mode of communication one of individual experts at the centre (as I am here on the podium) with questions to be asked, when allowed, from the periphery (you in the audience)?

Worse than that the system these chemists were using, ResearchGate is a western commercial infrastructures built from the classic Silicon Valley mindset, seeking to monetise, to in many ways to colonise, the interactions of these scholars who define themselves precisely through opposition to much of that culture. Is it possible to build a system that would help this group communicate within the scope of their culture but that doesn’t impose assumptions of our western culture? What infrastructures might be built that would achieve this and how would they be designed?

For Hartley and Potts the group, this level of analysis is one defined by shared culture. And of which cultures support groups which support the dynamic co- and re-creation of that culture. So another way of approaching this is to view them through the lens of the economics of clubs. What makes a club viable and sustainable? What goods does it use to achieve this? This group economics focus is interesting to me because it challenges many of our assumptions about the politics and economics of “Open”.

Rather than adopt a language of nationalisation of private goods: you journal publisher must give up your private property (articles) and transfer them to the public, you researcher must share your data with the world; we ask a different question – what is the club giving up and what are they gaining in return? Knowledge in this model is not a public good, but rather a club good – there is always some exclusion – that we are seeking to make more public through sharing. The political/economic (or advocacy) challenge is how to create an environment that tips the balance for clubs towards knowledge sharing.

These two questions – how can we support peripheral communities to co-create their own cultures without imposing ours and how we might change the economics of knowledge systems to favour investment in sharing – lead for me to an interesting suggestion and a paradox. What enabling infrastructures can be built and how can we make them as neutral and inclusive as possible while simultaneously embracing that anything built with western resources will be framed by our own cultures?

My stance on this is a re-statement of the concept from Zittrain, Benkler, Shirky and others that networks at scale can deliver new kinds of value. That the infrastructures we seek to build can tip the balance towards club investment in sharing if they provide mechanisms for clubs to gain access to networks. This is an architectural principle, that we can take a step up (or down if you prefer) identifying the common aspects of functionality required. It is also not new.

The new step is to adopt a principle of cultural engagement in governance, a means of – in the language of this conference – aligning the institutions that provide infrastructures and their governance and structures with the maximum possible number (and not power, not centrality) of cultures. The the criteria we use is one of maximising the number of productive interactions between cultures through the platforms we provide.

And this is what brings us back to Open, to what for me is the core of the philosophy, value system, or culture of Open Practice. Not that sharing outwards to the public is the target in itself but that it is through sharing that we create new opportunities for interaction and it is being open to contributions, to productive interactions that in my old world view creates value, but in this new framing promotes the “clashes of culture” that create new knowledge.

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On the 10th Anniversary of the Budapest Declaration

Budapest: Image from Wikipedia, by Christian Mehlführer

Ten years ago today, the Budapest Declaration was published. The declaration was the output of a meeting held some months earlier, largely through the efforts of Melissa Hagemann, that brought together key players from the, then nascent, Open Access movement. BioMedCentral had been publishing for a year or so, PLoS existed as an open letter, Creative Commons was still focussed on building a commons and hadn’t yet released its first licences. The dotcom bubble had burst, deflating many of the exuberant expectations of the first generation of web technologies and it was to be another year before Tim O’Reilly popularised the term “Web 2.0” arguably marking the real emergence of the social web.

In that context the text of the declaration is strikingly prescient. It focusses largely on the public good of access to research, a strong strand of the OA argument that remains highly relevant today.

“An old tradition and a new technology have converged to make possible an unprecedented public good. The old tradition is the willingness of scientists and scholars to publish the fruits of their research in scholarly journals without payment, for the sake of inquiry and knowledge. The new technology is the internet. The public good they make possible is the world-wide electronic distribution of the peer-reviewed journal literature and completely free and unrestricted access to it by all scientists, scholars, teachers, students, and other curious minds. Removing access barriers to this literature will accelerate research, enrich education, share the learning of the rich with the poor and the poor with the rich, make this literature as useful as it can be, and lay the foundation for uniting humanity in a common intellectual conversation and quest for knowledge.”

But at the same time, and again remember this is at the very beginning of the development of the user-generated web, the argument is laid out to support a networked research and discovery environment.

“…many different initiatives have shown that open access […] gives readers extraordinary power to find and make use of relevant literature, and that it gives authors and their works vast and measurable new visibility, readership, and impact.”

But for me, the core of the declaration lies in its definition. At one level it seems remarkable to have felt a need to define Open Access, and yet this is something we still struggle with this today. The definition in the Budapest Declaration is clear, direct, and precise:

“By ‘open access’ to this literature, we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited.”

Core to this definition are three things. Access to the text, understood as necessary to achieve the other aims; a limitation on restrictions and a limitation on the use of copyright to only support the integrity and attribution of the work – which I interpret in retrospect to mean the only acceptable licences are those that require attribution only. But the core forward looking element lies in the middle of the definition, focussing as it does on specific uses; crawling, passing to software as data, that would have seemed outlandish, if not incomprehensible, to most researchers at the time.

In limiting the scope of acceptable restrictions and in focussing on the power of automated systems, the authors of the Budapest declaration recognised precisely the requirements of information resources that we have more recently come to understand as requirements for effective networked information. Ten years ago, before Facebook existed, let alone before anyone was talking about frictionless sharing – the core characteristics were identified that would enable research outputs to be accessed and read, but above all integrated, mined, aggregated and used in ways that their creators did not, could not, expect. The core characteristics of networked information that enable research outputs to become research outcomes. The characteristics that will maximise the impact of that research.

I am writing this in a hotel room in Budapest. I am honoured to have been invited to attend a meeting to mark the 10th anniversary of the declaration and excited to be discussing what we have learnt over the past ten years and how we can navigate the next ten. The declaration itself remains as clear and relevant today as it was ten years ago. Its core message is one of enabling the use and re-use of research to make a difference. Its prescience in identifying exactly those issues that best support that aim in a networked world is remarkable.

In looking both backwards, over the achievements of the past ten years, and forwards, towards the challenges and opportunities that await us when true Open Access is achieved, the Budapest Declaration is, for me, the core set of principles that can guide us along the path to realising the potential of the web for supporting research and its wider place in society.

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Response to the RFI on Public Access to Research Communications

Have you written your response to the OSTP RFIs yet? If not why not? This is amongst the best opportunities in years to directly tell the U.S. government how important Open Access to scientific publications is and how to start moving to a much more data centric research process. You’d better believe that the forces of stasis, inertia, and vested interests are getting their responses in. They need to be answered.

I’ve written mine on public access and you can read and comment on it here. I will submit it tomorrow just in front of the deadline but in the meantime any comments are welcome. It expands on and discusses many of the same issues, specifically on re-configuring the debate on access away from IP and towards services, that have been in my recent posts on the Research Works Act.

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Designing for the phase change: Local communities and shared infrastructure

Pink crystal.
Image via Wikipedia

Michael Nielsen‘s talk at Science Online was a real eye opener for many of us who have been advocating for change in research practice. He framed the whole challenge of change as an example of a well known problem, that of collective action. How do societies manage big changes when those changes often represent a disadvantage to many individuals, at least in the short term. We can all see the global advantages of change but individually acting on them doesn’t make sense.

Michael placed this in the context of other changes, that of countries changing which side of the road they drive on, or the development of trade unions, that have been studied in some depth by political economists and similar academic disciplines. The message of these studies is that change usually occurs in two phases. First local communities adopt practice (or at least adopt a view that they want things changed in the case of which side of the road they drive on) and then these communities discover each other and “agglomerate”, or in the language of physical chemistry there are points of nucleation which grow to some critical level and then the whole system undergoes a phase change, crystallising into a new form.

These two phases are driven by different sets of motivations and incentives. At a small scale processes are community driven, people know each other, and those interactions can drive and support local actions, expectations, and peer pressure. At a large scale the incentives need to be different and global. Often top down policy changes (as in the side of the road) play a significant role here, but equally market effects and competition can also fall into place in a way that drives adoption of new tools or changes in behaviour. Think about the way new research techniques get adopted: first they are used by small communities, single labs, with perhaps a slow rate of spread to other groups. For a long time it’s hard for the new approach to get traction, but suddenly at some point either enough people are using it that its just the way things are done, or conversely those who are using it are moving head so fast that everyone else has to pile in just to keep up. It took nearly a decade for PCR for instance to gain widespread acceptance as a technique in molecular biology but when it did it went from being something people were a little unsure of to being the only way to get things done very rapidly.

So what does this tell us about advocating for, or designing for, change. Michael’s main point was that narrow scope is a feature, not a bug, when you are in that first phase. Working with small scale use cases, within communities is the way to get started. Build for those communities and they will become your best advocates, but don’t try to push the rate of growth, let it happen at the right rate (whatever that might be – and I don’t really know how to tell to be honest). But we also need to build in the grounding for the second phase.

The way these changes generally occur is through an accidental process of accretion and agglomeration. The phase change crystallises out around those pockets of new practice. But, to stretch the physical chemistry analogy, doesn’t necessarily crystallise in the form one would design for. But we have an advantage, if we design in advance to enable that crystallisation then we can prepare communities and prepare tooling for when it happens and we can design in the features that will get use closer to the optimum we are looking for.

What does this mean in practice? It means that when we develop tools and approaches it is more important for our community to have standards than it is for there to be an effort on any particular tool or approach. The language we use, that will be adopted by communities we are working with, should be consistent, so that when those communities meet they can communicate. The technical infrastructure we use should be shared, and we need interoperable standards to ensure that those connections can be made. Again, interchange and interoperability are more important than any single effort, any single project.

If we really believe in the value of change then we need to get these things together before we push them too hard into the diverse set of research communities where we want them to take root. We really need to get interoperability, standards, and language sorted out before the hammer of policy comes down and forces us into some sort of local minimum. In fact, it sounds rather like we have a collective action problem of our own. So what are we going to do about that?

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Submission to the Royal Society Enquiry

Title page of Philosophical Transactions of th...
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The Royal Society is running a public consultation exercise on Science as a Public Enterprise. Submissions are requested to answer a set of questions. Here are my answers.

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.

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Michael Nielsen, the credit economy, and open science

No credit cards please.......

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 research assessment (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. 

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.

 

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A collaborative proposal on research metrics

Measuring time
Image by aussiegall via Flickr

tldr: Proposed project to connect metrics builders with those who can most effectively use them to change practice. Interested? Get involved! Proposal doc is here and free to edit.

When we talk about open research practice, more efficient research communication, wider diversity of publication we always come up against the same problem. What’s in it for the jobbing scientist? This is so prevalent that it has been reformulated as “Singh’s Law” (by analogy with Godwin’s law) that any discussion of research practice will inevitably end when someone brings up career advancement or tenure. The question is what do we actually do about this?

The obvious answer is to make these things matter. Research funders have the most power here in that they have the power to influence behaviour through how they distribute resources. If the funder says something is important then the research community will jump to it. The problem of course it that in practice funders have to take their community with them. Radical and rapid change is not usually possible. A step in the right direction would be to provide funders and researchers with effective means of measuring and comparing themselves and their outputs. In particular means of measuring performance in previously funded activities.

There are many current policy initiatives on trying to make these kinds of judgements. There are many technical groups building and discussing different types of metrics. Recently there have also been calls to ensure that the data that underlies these metrics is made available. But there is relatively little connection between these activities. There is an opportunity to connect technical expertise and data with the needs of funders, researchers, and perhaps even the mainstream media and government.

An opportunity has arisen for some funding to support a project here. My proposal is to bring a relevant group of stakeholders together; funders, technologists, scientists, adminstrators, media, publishers, and aggregators, to identify needs and then to actually build some things. Essentially the idea is a BarCamp style day and a bit meeting followed by a two day hackfest. Following on from this the project would fund some full time effort to take the most promising ideas forward.

I’m looking for interested parties. This will be somewhat UK centric just because of logistics and funding but the suggestion has already been made that following up with a similar North American or European project could be interesting. The proposal is available to view and edit as a GoogleDoc. Feel free to add your name, contact me directly, or suggest the names of others (probably better to me directly). I have a long list of people to contact directly as well but feel free to save me the effort.

Ed. Note: This proposal started as a question on Friendfeed where I’ve already got a lot of help and ideas. Hopefully soon I will write another post about collaborative and crowdsourced grant writing and how it has changed since the last time I tried this some years back.

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It wasn’t supposed to be this way…

I’ve avoided writing about the Climate Research Unit emails leak for a number of reasons. Firstly it is clearly a sensitive issue with personal ramifications for some and for many others just a very highly charged issue. Probably more importantly I simply haven’t had the time or energy to look into the documents myself. I haven’t, as it were, examined the raw data for myself, only other people’s interpretations. So I’ll try to stick to a very general issue here.

There are appear to be broadly two responses from the research community to this saga. One is to close ranks and to a certain extent say “nothing was done wrong here”. This is at some level, the tack taken by the Nature Editorial of 3 December, which was headed up with “Stolen e-mails have revealed no scientific conspiracy…”. The other response is that the scandal has exposed the shambolic way that we deal with collecting, archiving, and making available both data and analysis in science, as well as the endemic issues around the hoarding of data by those who have collected it.

At one level I belong strongly in the latter camp, but I also appreciate the dismay that must be felt by those who have looked at, and understand what the emails actually contain, and their complete inability to communicate this into the howling winds of what seems to a large extent a media beatup. I have long felt that the research community would one day be shocked by the public response when, for whatever reason, the media decided to make a story about the appalling data sharing practices of publicly funded academic researchers like myself. If I’d thought about it more deeply I should have realised that this would most likely be around climate data.

Today the Times reports on its front page that the UK Metererology Office is to review 160 years of climate data and has asked a range of contributing organisations to allow it to make data public. The details of this are hazy but if the UK Met Office is really going to make the data public this is a massive shift. I might be expected to be happy about this but I’m actually profoundly depressed. While it might in the longer term lead to more strongly worded and enforced policies it will also lead to data sharing being forever associated with “making the public happy”. My hope has always been that the sharing of the research record would come about because people started to see the benefits, because they could see the possibilities in partnership with the wider community, and that it made their research more effective. Not because the tabloids told us we should.

Collecting the best climate data and doing the best possible analysis on it is not an option. If we get this wrong and don’t act effectively then with some probability that is significantly above zero our world ends. The opportunity is there to make this the biggest, most important, and most effective research project ever undertaken. To actively involve the wider community in measurement. To get an army of open source coders to re-write, audit, and re-factor the analysis software. Even to involve the (positively engaged) sceptics, to use their interest and ability to look for holes and issues. Whether politicians will act on data is not the issue that the research community can or should address; what we need to be clear on is that we provide the best data, the best analysis, and an honest view of the uncertainties. Along with the ability of anyone to critically analyse the basis for those conclusions.

There is a clear and obvious problem with this path. One of the very few credible objections to open research that I have come across is that by making material available you open your inbox to a vast community of people who will just waste your time. The people who can’t be bothered to read the background literature or learn to use the tools; the ones who just want the right answer. This is nowhere more the case than it is with climate research and it forms the basis for the most reasonable explanation of why the CRU (and every other repository of climate data as far as I am aware) have not made more data or analysis software directly available.

There are no simple answers here, and my concern is that in a kneejerk response to suddenly make things available no-one will think to put in place the social and technical infrastructure that we need to support positive engagement, and to protect active researchers, both professional and amateur from time-wasters. Interestingly I think this infrastructure might look very similar to that which we need to build to effectively share the research we do, and effectively discover the relevant work of others. Infrastructure is never sexy, particularly in the middle of a crisis. But there is one thing in the practice of research that we forget at our peril. Any given researcher needs to earn the right to be taken seriously. No-one ever earns the right to shut people up. Picking out the objection that happens to be important is something we have to at least attempt to build into our systems.

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Open Research: The personal, the social, and the political

Next Tuesday I’m giving a talk at the Institute for Science Ethics and Innovation in Manchester. This is a departure for me in terms of talk subjects, in as much as it is much more to do with policy and politics. I have struggled quite a bit with it so this is an effort to work it out on “paper”. Warning, it’s rather long. The title of the talk is “Open Research: What can we do? What should we do? And is there any point?”

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I’d like to start by explaining where I’m coming from. This involves explaining a bit about me. I live in Bath. I work at the Rutherford Appleton Laboratory, which is near Didcot. I work for STFC but this talk is a personal view so you shouldn’t take any of these views as representing STFC policy. Bath and Didcot are around 60 miles apart so each morning I get up pretty early, I get on a train, then I get on a bus which gets me to work. I work on developing methodology to study complex biological structures. We have a particular interest in trying to improve methods for looking at proteins that live in biological membranes and protein-nucleic acid complexes. I also have done work on protein labelling that lets us make cool stuff and pretty pictures. This work involves an interesting mixture of small scale lab work, work at large facilities on big instruments, often multi-national facilities. It also involves far too much travelling.

A good question to ask at this point is “Why?” Why do I do these things? Why does the government fund me to do them? Actually it’s not so much why the government funds them as why the public does. Why does the taxpayer support our work? Even that’s not really the right question because there is no public. We are the public. We are the taxpayer. So why do we as a community support science and research? Historically science was carried out by people sufficiently wealthy to fund it themselves, or in a small number of cases by people who could find wealth patrons. After the second world war there was a political and social concensus that science needed to be supported and that concensus has supported research funding more or less to the present day. But with the war receding in public memory we seem to have retained the need to frame the argument for research funding in terms of conflict or threat. The War on Cancer, the threat of climate change. Worse, we seem to have come to believe our own propaganda, that the only way to justify public research funding is that it will cure this, or save us from that. And the reality is that in most cases we will probably not deliver on this.

These are big issues and I don’t really have answers to a lot them but it seems to me that they are important questions to think about. So here are some of my ideas about how to tackle them from a variety of perspectives. First the personal.

A personal perspective on why and how I do research

My belief is we have to start with being honest with ourselves, personally, about why and how we do research. This sounds like some sort of self-help mantra I know but let me explain what I mean. My personal aim is to maximise my positive impact on the world, either through my own work or through enabling the work of others. I didn’t come at this from first principles but it has evolved. I also understand I am personally motivated by recognition and reward and that I am strongly, perhaps too strongly, motivated by others opinions of me. My understanding of my own skills and limitations means that I largely focus my research work on methodology development and enabling others. I can potentially have a bigger impact by building systems and capabilities that help others do their research than I can by doing that research myself. I am lucky enough to work in an organization that values that kind of contribution to the research effort.

Because I want my work to be used as far as is possible I make as much as possible of it freely available. Again I am lucky that I live now when the internet makes this kind of publishing possible. We have services that enable us to easily publish ideas, data, media, and process and I can push a wide variety of objects onto the web for people to use if they so wish. Even better than that I can work on developing tools and systems that help other people to do this effectively. If I can have a bigger impact by enabling other peoples research then I can multiply that again by helping other people to share that research. But here we start to run into problems. Publishing is easy. But sharing is not so easy. I can push to the web, but is anyone listening? And if they are, can they understand what I am saying?

A social perspective (and the technical issues that go with it)

If I want my publishing to be useful I need to make it available to people in a way they can make use of. We know that networks increase in value as they grow much more than linearly. If I want to maximise my impact, I have to make connections and maximise the ability of other people to make connections. Indeed Merton made the case for this in scientific research 20 years ago.

I propose the seeming paradox that in science, private property is established by having its substance freely given to others who might want to make use of it.

This is now a social problem but a social problem with a distinct technical edge to it.  Actually we have two related problems. The issue of how I make my work available in a useful form and the separate but related issue of how I persuade others to make their work available for others to use.

The key to making my work useful is interoperability. This is at root a technical issue but at a purely technical level is one that has been solved. We can share through agreed data formats and vocabularies. The challenges we face in actually making it happen are less technical problems than social ons but I will defer those for the moment. We also need legal interoperability. Science Commons amongst others has focused very hard on this question and I don’t want to discuss it in detail here except to say that I agree with the position that Science Commons takes; that if you want to maximise the ability of others to re-use your work then you must make it available with liberal licences that do not limit fields of use or the choice of license on derivative works. This mean CC-BY, BSD etc. but if you want to be sure then your best choice is explicit dedication to the public domain.

But technical and legal interoperability are just subsets of what I think is more important;  process interoperability. If the object we publish are to be useful then they must be able to fit into the processes that researchers actually use. As we move to the question of persuading others to share and build the network this becomes even more important. We are asking people to change the way they do things, to raise their standards perhaps. So we need to make sure that this is as easy as possible and fits into their existing workflows. The problem with understanding how to achieve technical and legal interoperability is that the temptation is to impose it and I am as guilty of this as anyone. What I’d like to do is use a story from our work to illustrate an approach that I think can help us to make this easier.

Making life easier by capturing process as it happens: Objects first, structure later

Our own work on web based laboratory recording systems, which really originates in the group of Jeremy Frey at Southampton came out of earlier work on a fully semantic RDF backed system for recording synthetic chemistry. In contrast we took an almost completely unstructured approach to recording work in a molecular biology laboratory, not because we were clever or knew it would work out, but because it was a contrast to what had gone before. The LaBLog is based on a Blog framework and allows the user to put in completely free text, completely arbitrary file attachments, and to organize things in whichever way they like. Obviously a recipe for chaos.

And it was to start with as we found our way around but we went through several stages of re-organization and interface design over a period of about 18 months. The key realization we made was that while a lot of what we were doing was difficult to structure in advance that there were elements within that, specific processes, specific types of material that were consistently repeated, even stereotyped, and that structuring these gave big benefits. We developed a template system that made producing these repeated processes and materials much easier. These templates depended on how we organized our posts, and the metadata that described them, and the metadata in turn was driven by the need for the templates to be effective. A virtuous circle developed around the positive re-inforcement that the templates and associated metadata provided. More suprisingly the structure that evolved out of this matched in many cases well onto existing ontologies. In specific cases where it didn’t we could see that either the problem arose from the ontology itself, or the fact that our work simply wasn’t well mapped by that ontology. But the structure arose spontaneously out of a considered attempt to make the user/designer’s life easier. And was then mapped onto the external vocabularies.

I don’t want to suggest that our particular implementation is perfect. It is far from it, with gaping holes in the usability and our ability to actually exploit the structure that has developed. But I think the general point is useful. For the average scientist to be willing to publish more of their research, that process has to be made easy and it has to recognise the inherently unstructured nature of most research. We need to apply structured descriptions where they make the user’s life easier but allow unstructured or semi-structured representations elsewhere. But we need to build tools that make it easy to take those unstructured or semi-structure records and mold them into a specific structured narrative as part of a reporting process that the researcher has to do anyway. Writing a report, writing a paper. These things need to be done anyway and if we could build tools so that the easiest way to write the report or paper is to bring elements of the original record together and push those onto the web in agreed formats through easy to use filters and aggregators then we will have taken an enormous leap forward.

Once you’ve insinuated these systems into the researchers process then we can start talking about making that process better. But until then technical and legal interoperability are not enough – we need to interoperate with existing processes as well. If we could achieve this then much more research material would flow online, connections would be formed around those materials, and the network would build.

And finally – the political

This is all very well. With good tools and good process I can make it easier for people to use what I publish and I can make it easier for others to publish. This is great but it won’t make others want to publish. I believe that more rapid publication of research is a good thing. But if we are to have a rational discussion about whether this is true we need to have agreed goals. And that moves the discussion into the political sphere.

I asked earlier why it is that we do science as a society, why we fund it. As a research community I feel we have no coherent answer to these questions.  I also talked about being honest to ourselves. We should be honest with other researchers about what motivates us, why we choose to do what we do, and how we choose to divide limited resources. And as recipients of taxpayers money we need to be clear with government and the wider community about what we can achieve. We also have an obligation to optimize the use of the money we spend. And to optimize the effective use of the outputs derived from that money.

We need at core a much more sophisticated conversation with the wider community about the benefits that research brings; to the economy, to health, to the environment, to education. And we need a much more rational conversation within the research community as to how those different forms of impact are and should be tensioned against each other.  We need in short a complete overhaul if not a replacement of the post-war concensus on public funding of research. My fear is that without this the current funding squeeze will turn into a long term decline. And that without some serious self-examination the current self-indulgent bleating of the research community is unlikely to increase popular support for public research funding.

There are no simple answers to this but it seems clear to me that at a minimum we need to be demonstrating that we are serious about maximising the efficiency with which we spend public money. That means making sure that research outputs can be re-used, that wheels don’t need to re-invented, and innovation flows easily from the academic lab into the commercial arena. And it means distinguishing between the effective use of public money to address market failures and subsidising UK companies that are failing to make effective investments in research and development.

The capital generated by science is in ideas, capability, and people. You maximise the effective use of capital by making it easy to move, by reducing barriers to trade. In science we can achieve this by maximising the ability transfer research outputs. If we to be taken seriously as guardians of public money and to be seen as worthy of that responsibility our systems need to make ideas, data, methodology, and materials flow easily. That means making our data, our process, and our materials freely available and interoperable. That means open research.

We need a much greater engagement with the wider community on how science works and what science can do. The web provides an immense opportunity to engage the public in active research as demonstrated by efforts as diverse as Galaxy Zoo with 250,000 contributors and millions of galaxy classifications and the Open Dinosaur Project with people reading online papers and adding the measurements of thigh bones to an online spreadsheet. Without the publicly available Sloan Digital Sky Survey, without access to the paleontology papers, and without the tools to put the collected data online and share them these people, this “public”, would be far less engaged. That means open research.

And finally we need to turn the tools of our research on ourselves. We need to critically analyse our own systems and processes for distributing resources, for communicating results, and for apportioning credit. We need to judge them against the value for money they offer to the taxpayer and where they are found wanting we need to adjust. In the modern networked world we need to do this in a transparent and honest manner. That means open research.

But even if we agree these things are necessary, or a general good, they are just policy. We already have policies which are largely ignored. Even when obliged to by journal publication policies or funder conditions researchers avoid, obfuscate, and block attempts to gain access to data, materials, and methdology. Researchers are humans too with the same needs to get ahead and to be recognized as anyone else. We need to find a way to map those personal needs, and those personal goals, onto the community’s need for more openness in research. As with the tooling we need to “bake in” the openness to our processes to make it the easiest way to get ahead. Policy can help with cultural change but we need an environment in which open research is the simplest and easiest approach to take. This is interoperability again but in this case the policy and process has to interoperate with the real world. Something that is often a bit of a problem.

So in conclusion…

I started with a title I’ve barely touched on.  But I hope with some of the ideas I’ve explored we are in a position to answer the questions I posed. What can we do in terms of Open Research? The web makes it technically possible for us the share data, process, and records in real time. It makes it easier for us to share materials though I haven’t really touched on that. We have the technical ability to make that data useful through shared data formats and vocabularies. Many of the details are technically and socially challenging but we can share pretty much anything we choose to on a wide variety of timeframes.

What should we do? We should make that choice easier through the development of tools and interfaces that recognize that it is usually humans doing and recording the research and exploiting the ability of machines to structure that record when they are doing the work. These tools need to exploit structure where it is appropriate and allow freedom where it is not. We need tools to help us map our records onto structures as we decide how we want to present them. Most importantly we need to develop structures of resource distribution, communication, and recognition that encourage openness by making it the easiest approach to take. Encouragement may be all that’s required. The lesson from the web is that once network effects take hold they can take care of the rest.

But is there any point? Is all of this worth the effort? My answer, of course, is an unequivocal yes. More open research will be more effective, more efficient, and provide better value for the taxpayer’s money. But more importantly I believe it is the only credible way to negotiate a new concensus on the public funding of research. We need an honest conversation with government and the wider community about why research is valuable, what the outcomes are, and how the contribute to our society. We can’t do that if the majority cannot even see those outcomes. The wider community is more sophisticated that we give it credit for. And in many ways the research community is less sophisticated than we think. We are all “the public”. If we don’t trust the public to understand why and how we do research, if we don’t trust ourselves to communicate the excitement and importance of our work effectively, then I don’t see why we deserve to be trusted to spend that money.