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EC Consultation on open research data

- July 17, 2013 in Featured, Open Access, Open Data

The European Commission held a public consultation on open access to research data on July 2 in Brussels inviting statements from researchers, industry, funders, IT and data centre professionals, publishers and libraries. The inputs of these stakeholders will play some role in revising the Commission’s policy and are particularly important for the ongoing negotiations on the next big EU research programme Horizon 2020, where about 25-30 billion Euros would be available for academic research. Five questions formed the basis of the discussion:

  • How we can define research data and what types of research data should be open?
  • When and how does openness need to be limited?
  • How should the issue of data re-use be addressed?
  • Where should research data be stored and made accessible?
  • How can we enhance “data awareness” and a “culture of sharing”?

Here is how the Open Knowledge Foundation responded to the questions:

How can we define research data and what types of research data should be open?

Research data is extremely heterogeneous, and would include (although not be limited to) numerical data, textual records, images, audio and visual data, as well as custom-written software, other code underlying the research, and pre-analysis plans. Research data would also include metadata – data about the research data itself – including uncertainties and methodology, versioned software, standards and other tools. Metadata standards are discipline-specific, but to be considered ‘open’, at a bare minimum it would be expected to provide sufficient information that a fellow researcher in the same discipline would be able to interpret and reuse the data, as well as be itself openly available and machine-readable. Here, we are specifically concerned with data that is being produced, and therefore can be controlled by the researcher, as opposed to data the researcher may use that has been produced by others.

When we talk about open research data, we are mostly concerned with data that is digital, or the digital representation of non-digital data. While primary research artifacts, such as fossils, have obvious and substantial value, the extent to which they can be ‘opened’ is not clear. However, the use of 3D scanning techniques can and should be used to enable the capture of many physical features or an image, enabling broad access to the artifact. This would benefit both researchers who are unable to travel to visit a physical object, as well as interested citizens who would typically be unable to access such an item.

By default there should be an expectation that all types of research data that can be made public, including all metadata, should be made available in machine-readable form and open as per the Open Definition. This means the data resulting from public work is free for anyone to use, reuse and redistribute, with at most a requirement to attribute the original author(s) and/or share derivative works. It should be publicly available and licensed with this open license.

When and how does openness need to be limited?

The default position should be that research data should be made open in accordance with the Open Definition, as defined above. However, while access to research data is fundamentally democratising, there will be situations where the full data cannot be released; for instance for reasons of privacy.

In these cases, researchers should share analysis under the least restrictive terms consistent with legal requirements, and abiding by the research ethics as dictated by the terms of research grant. This should include opening up non-sensitive data, summary data, metadata and code; and providing access to the original data available to those who can ensure that appropriate measures are in place to mitigate any risks.

Access to research data should not be limited by the introduction of embargo periods, and arguments in support of embargo periods should be considered a reflection of inherent conservatism among some members of the academic community. Instead, the expectation should be that data is to be released before the project that funds the data production has been completed; and certainly no later than the publication of any research output resulting from it.

How should the issue of data re-use be addressed?

Data is only meaningfully open when it is available in a format and under an open license which allows re-use by others. But simply making data available is often not sufficient for reusing it. Metadata must be provided that provides sufficient documentation to enable other researchers to replicate empirical results.

There is a role here for data publishers and repository managers to endeavour to make the data usable and discoverable by others. This can be by providing further documentation, the use of standard code lists, etc., as these all help make data more interoperable and reusable. Submission of the data to standard registries and use of common metadata also enable greater discoverability. Interoperability and the availability of data in machine-readable form are crucial to ensure data-mining and text-mining of the data can be performed, a form of re-use that must not be restricted.

Arguments are sometimes made that we should monitor levels of data reuse, to allow us to dynamically determine which data sets should be retained. We refute this suggestion. There is a moral responsibility to preserve data created by taxpayer funds, including data that represents negative results or that is not obviously linked to publications. It is impossible to predict possible future uses, and reuse opportunities may currently exist that may not be immediately obvious. It is also crucial to note the research interests change over time.

Where should research data be stored and made accessible?

Each discipline needs different options available to store data and open it up to their community and the world; there is no one-size-fits-all solution. The research data infrastructure should be based on open source software and interoperable based on open standards. With these provisions we would encourage researchers to use the data repository that best fits their needs and expectations, for example an institutional or subject repository. It is crucial that appropriate metadata about the data deposited is stored as well, to ensure this data is discoverable and can be re-used more easily.

Both the data and the metadata should be openly licensed. They should be deposited in machine-readable and open formats, similar to how the US government mandate this in their Executive Order on Government Information. This ensures the possibility to link repositories and data across various portals and makes it easier to find the data. For example, the open source data portal CKAN has been developed by the Open Knowledge Foundation, which enables the depositing of data and metadata and makes it easy to find and re-use data. Various universities, such as the Universities of Bristol and Lincoln, already use CKAN for these purposes.

How can we enhance data awareness and a culture of sharing?

Academics, research institutions, funders, and learned societies all have significant responsibilities in developing a culture of data sharing. Funding agencies and organisations disbursing public funds have a central role to play and must ensure research institutions, including publicly supported universities, have access to appropriate funds for longer-term data management. Furthermore, they should establish policies and mandates that support these principles.

Publication and, more generally sharing, of research data should be ingrained in the academic culture, and should be seen as a fundamental part of scholarly communication. However, it is often seen as detrimental to a career, partly as a result of the current incentive system set up by by universities and funders, partly as a result of much misunderstanding of the issues.

Educational and promotional activities should be set up to promote the awareness of open access to research data amongst researchers, to help disentangle the many myths, and to encourage them to self-identify as supporting open access. These activities should be set up in recognition of the fact that different disciplines are at different stages in the development of the culture of sharing. Simultaneously, universities and funders should explore options for creating incentives to encourage researchers to publish their research data openly. Acknowledgements of research funding, traditionally limited to publications, could be extended to research data and contribution of data curators should be recognised.

References

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Open Access to Research Data: The European Commission’s consultation in progress

- July 9, 2013 in Featured, Open Access, Open Research

The European Commission held a public consultation on open access to research data on July 2 in Brussels inviting statements from researchers, industry, funders, IT and data centre professionals, publishers and libraries. The inputs of these stakeholders will play some role in revising the Commission’s policy and are particularly important for the ongoing negotiations on the next big EU research programme Horizon 2020, where about 25-30 billion Euros would be available for academic research. Five questions formed the basis of the discussion:

  • How we can define research data and what types of research data should be open?
  • When and how does openness need to be limited?
  • How should the issue of data re-use be addressed?
  • Where should research data be stored and made accessible?
  • How can we enhance “data awareness” and a “culture of sharing”?

Contributions from the researchers’ perspective emphasised that data, metadata and other documentation should be made available in order to be able to replicate the results of a research article and more data available means more scrutiny and getting more value out of the data. Furthermore, there is a need for pre-registration of studies in order to understand the full picture of a research field where e.g. negative results in the biomedical sciences (as well as many other fields) are not published. Then, this is also a need to have binding mechanisms e.g. required data management plans, better linkage between the research data and scientific publication with enforcement of data availability by journals, but also sustainable plans for making data available, where open access to data is formally a part of the research budget.

Searching and finding research data should be also made easier, as open access to data does not necessarily mean accessible data. There was also an emphasis that every contributor should be known and acknowledged and there is a need of establishing cultures around data sharing in different disciplines and “augmenting the scientific infrastructure to be technical, social and participatory” (Salvatore Mele, CERN).

There was some agreement that commercial data and data which can lead back to individuals should be kept closed but some aggregated data should be shared. Industry representatives (Philips Research, Federation of German Security and Defence Industries) argued for keeping some data closed, deciding on a case by case basis and having embargo periods on data produced in public-private partnerships in order to encourage investment.

Funders viewed research data as a public good, which should be managed and be discoverable, and encouraged open and better access to research data where research outputs are accessed and used in a way that maximises the public benefit. While there is a growing consensus about funder policies, these should be better implemented and enforced. Resources like – infrastructure, incentives and cultures, capacity and skills, ethics and governance – should be built and sustained in recognition of the different stages that different disciplines are currently at (some really good points made by David Carr, the Wellcome Trust).

The IT, data centre professionals and librarians spoke about the need to recognise the role of data scientists and data librarians, with appropriate funding and careers. While the value of data is often recognised later on and grows over time there is less of an understanding who would pay for the long-term preservation since few institutions can make indefinite commitments. A key component should be also proper training and the development of core skills in dealing with research data (where librarians can assist researchers in data management plans, bridging the gap in knowledge), as well as the proper citation rules and practices for data where career recognition can be linked to sharing of research data in order to boost incentives.

While the European Commission has been carrying the flag of open access, mandating open access to research publications funded by the last research and innovation programme FP7, there are larger hurdles on the road to open access to research data. While the EC’s communication “Towards better access to scientific information” reflects some commitment to open access to research data, there are many exceptions, e.g. privacy, trade secrets, national security, legitimate commercial interest, intellectual property, data resulting from a public-private partnership, etc. As Mireille van Echoud, professor of Information Law at IViR, stated at the Open Economics workshop in June, “any lawyer will find whatever argument they need to keep data from falling under an open access obligation”.

Look at some more detailed notes from Ian Mulvany and his presentation on the behalf of several publishers.

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Open Access Economics: To share or not to share?

- May 22, 2013 in Featured, Open Access, Open Data, Open Economics, Open Research

Last Friday, Barry Eichengreen, professor of Economics and Political Science at Berkeley, wrote about “Open Access Economics” at the prestigious commentary, analysis and opinion page Project Syndicate, where influential professionals, politicians, economists, business leaders and Nobel laureates share opinions about current economic and political issues.

He reaffirmed that indeed the results of the Reinhart and Rogoff study were used by some politicians to justify austerity measures taken by governments around the world with stifling public debt.

Professor Eichengreen also criticised the National Bureau of Economic Research (NBER) for failing to require data and code for the “flawed study” of the Harvard economists, which appeared first in the distinguished working paper series of NBER.

In line with the discussion we started at the LSE Social Impact Blog and the New Scientist, Barry Eichengreen brought home the message that indeed the enforcement of a data availability would have made a difference in this case.

At the same time, some express doubts about the need to share data and think about excuses to avoid sharing the data related to their publication. Economists at the anonymous web forum Econjobrumors.com have been joking about the best ways to avoid sharing data.

Here are some of “creative” suggestions on how the anonymous author could get around sending their data:

“Refer him to your press secretary”
“Tell him you had a computer virus that wiped out the dataset”
“Not obliged to let anyone free ride. Can you explain it like that?”
“Tell him its proprietary data and you can’t share it without having to kill him.”
“Tell him, ‘I’ll show you mine if you show me yours.”
“…say you signed NDA.”
“Huddle in the corner of your office wrapped in a blanket and some hot coco from the machine down the hall and wait for the inevitable.”
“Don’t reply.”

Anonymous author: “No, did not make up the results. But let’s just say you really do not want to play with the data in any way. No good for significance.”
Anonymous comment: “Added a couple of extra stars for good luck?”.

While many of the discussions on the anonymous blog are employing humour and jokes, this discussion reflects a mainstream attitude towards data sharing. It also shows how uncertain are some authors of the robustness of their results – even if they did not make any Reinhart and Rogoff excel mistakes, they are hesitating about sharing lest closer scrutiny would expose weaker methodology. Maybe more disclosure – there data can be shared – could improve the way research is done.

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Securing the Knowledge Foundations of Innovation

- May 15, 2013 in Advisory Panel, Featured, Open Access, Open Data, Open Research

Last month, Paul David, professor of Economics at Stanford University, Senior Fellow of the Stanford Institute for Economic Policy Research (SIEPR) and a member of the Advisory Panel delivered a keynote presentation at the International Seminar of the PROPICE in Paris.

Professor David expresses concern that the increased use of intellectual property rights (IPR) protections “has posed problems for open collaborative scientific research” and that the IPR regime has been used by businesses e.g. to “raise commercial rivals’ costs”, where empirical evidence shows has shown that business innovation is “is being inhibited by patent thickets”.

In describing the anti-commons issue, professor David also pointed out that research databases are likely sites for problems and emphasised the importance of protecting the future open access to critical data.

Also, high quality data would be very costly, where “…strengthening researchers’ incentives to create transparent, fully documented and dynamically annotated datasets to be used by others remains an insufficiently addressed problem”.

Read the whole presentation below:


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Publish open access, free of charge

- February 19, 2013 in Featured, Open Access, Open Economics, Open Research

Here at the Open Knowledge Foundation we think that open access is great. It’s cost-free to readers, and thus knowledge can be read, shared and re-used across the world without impediment.
But publishing itself isn’t cost free, and the costs of publishing must be supported somehow. The fear of expensive charges sometimes discourages academics from attempting to publish in OA journals. Indeed some traditional publishers charge huge fees to make an article open access e.g. the $5000 that Cell Press journals (Elsevier) charge.

Open access journal publishing doesn’t have to be this expensive though. To encourage economists to publish in Open Access journals, the IZA – Institute for the Study of Labor are kindly covering the cost of OA publishing for articles submitted to the 5 journals in the IZA Journal Series published by SpringerOpen. The only additional requirement stated is a reasonable one: “Authors are expected to actively support the IZA journals by refereeing a certain number of articles.”

 

The IZA open access journals

The requirement to review other articles in-turn is not unique to these journals. In STM publishing, an exciting new Open Access journal called PeerJ is also using this requirement to keep costs down. Arranging peer review is often cited as an expensive component of journal publishing, thus by requiring a pool of authors to provide reviews (if they are appropriate reviewers) it should help minimize overall costs to the publishing company.

PeerJ – a new science journal that’s touted for big things this year. Just $99 for OA publishing services

There are of course other excellent open access journal publishing options in economics available and some of these are reviewed here. We support all quality open access journal publishers and repositories.

The official announcement about this by Klaus F. Zimmermann, Editor-in-Chief of the IZA Journal Series is available here.

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Looking again at “Big Deal” scholarly journal packages

- February 18, 2013 in Contribution Economy, Economic Publishing, Featured, Open Access, Open Economics

This blog post is cross-posted from the Contribution Economy Blog.

One of the things pointed to in the debate over market power and scholarly journals is the rise of “Big Deal” packages. Basically, this has arisen as publishers bundle journals together for a single price. Indeed, as the publishers have merged and acquired more titles, these bundled packages have become more compelling with individual journal subscription pricing to libraries rising at a higher rate. This means that libraries with limited budgets are driven to give a greater share of their journal budgets to larger publishers; squeezing out smaller ones. The claim is that this is reducing choice.

While it is reducing choice amongst publishers, Andrew Odlyzko, in a recent paper, points out that “Big Deals” have also increased the number of journal titles available; not just in large libraries but across the board.

Serials

The reason is basically the same reason that is behind the drive towards open access — in electronic form, the marginal cost of an additional journal is zero and so it make sense to provide more journal titles to each library. Moreover, for smaller libraries, the average cost of a journal title has fallen at a faster rate than it has done for larger libraries. In other words, behind the spectre of increased publisher profits and market power, is an increase in journal availability. Put simply, more researchers have easier access to journals than before. This is one case where — if we just consider University libraries — price discrimination (using Varian’s rule) looks to be in the welfare improving range.

But there are, of course, wrinkles to all of this. This says nothing of access beyond Universities which is still an issue both economically and increasingly morally. It also says nothing of the distribution of rents in the industry. Publisher profits have increased dramatically and that money has to come from somewhere.

Odlyzko raises a new issue in that regard: publisher profits are a symptom that libraries are being squeezed. Of course, we know that the share of library budgets devoted to journal acquisition has risen. At the same time, library budgets have fallen although not as quickly as Odlyzko expected a decade ago. The reason is that libraries command attention at Universities. Changes to them are a signal of how quickly changes can occur within Universities. As it turns out, there is not very much. Libraries are centrally located, have nostalgic views in the eyes of alumni donors and hitting their budgets can often be read as a sign of a move against scholarship.

But what publishers are providing now, in terms of electronic access and search, is as much a transfer of functions as it is of money from libraries to themselves. Put simply, publishers are now doing what librarians used to do. They have provided tools that make it easier for people to find information. It is another way machines are being substituted for labor.

The competition between libraries and publishers has implications with regard to how we view alternative journal business models. Take, for instance, the notion that we can have journals funded by author fees and be given open access instead of being funded by user fees. If we did this, then this will just change the locus of the competitive fight between libraries and publishers to involve academics. Academics can legitimately argue that these new publication fees should come from the institution and, where will the institution find the money? In the now relieved library budgets as more journals go open access. So either way, the money for journal publishing will end up coming from libraries.

This is not to say that there is no scope for reducing the costs of journal access and storage. It is surely bloated now as it includes the publisher market power premium. The point is that libraries spent time resisting changes to journal business models as much as publishers did but that seems to have been a political error on their part.

This is all familiar stuff to economists. The flow of money is less important than the structure of activities. When it comes down to it, we know one thing: we can provide a journal system with labor from academics (as writers, referees and editors) and publisher activities when there is enough willingness to pay for all of it. That means we can provide the same overall payment and still, because journals are a non-rival good, have open access. In other words, there is no market impediment to open access, it is proven to be a pure Pareto improvement. The question now is how to do the “Really Big Deal” to get it there.

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Joshua Gans Joining the Advisory Panel of the Working Group

- February 14, 2013 in Advisory Panel, Contribution Economy, Featured, Open Access, Open Data, Open Economics

We are happy to welcome Joshua Gans in the Advisory Panel of the Open Economics Working Group.

Joshua Gans

Joshua Gans is a Professor of Strategic Management and holder of the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship at the Rotman School of Management, University of Toronto (with a cross appointment in the Department of Economics). Prior to 2011, he was the foundation Professor of Management (Information Economics) at the Melbourne Business School, University of Melbourne and prior to that he was at the School of Economics, University of New South Wales. In 2011, Joshua was a visiting researcher at Microsoft Research (New England). Joshua holds a Ph.D. from Stanford University and an honors degree in economics from the University of Queensland. In 2012, Joshua was appointed as a Research Associate of the NBER in the Productivity, Innovation and Entrepreneurship Program.

At Rotman, he teaches MBA and Commerce students Network and Digital Market Strategy. Most recently, he has written an eBook, Information Wants to be Shared (Harvard Business Review Press). While Joshua’s research interests are varied he has developed specialities in the nature of technological competition and innovation, economic growth, publishing economics, industrial organisation and regulatory economics. In 2007, Joshua was awarded the Economic Society of Australia’s Young Economist Award. In 2008, Joshua was elected as a Fellow of the Academy of Social Sciences, Australia. Details of his research activities can be found here. In 2011, Joshua (along with Fiona Murray of MIT) received a grant for almost $1 million from the Sloan Foundation to explore the Economics of Knowledge Contribution and Distribution.

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Can we have open data without open access?

- February 11, 2013 in Events, Featured, Open Access, Open Data, Open Economics, Open Research

Many of the motivations which drive open access are similar to why we want open data in social science research: making one’s research more widely available to the research community and to the wider public, producing more and better research that can be reproduced and verified.

openaccess

Photo by biblioteekje

On February 7-8, the University of Minho hosted the OpenAIRE Interoperability workshop, inviting academics, repository managers, publishers, funders, national help desks and open science advocates to discuss the challenge of interoperability in the emerging open access infrastructures.

Reviewing some of the reasons for open access, one would see that they are the same as for open data. Eloy Rodriguez (University of Minho Documentation Services) presented the drivers for open access what came in the discussion like the monitoring and assessment of research output, the visibility and impact, the economic benefits including innovation, the empowerment of institutions to preserve their own research outputs and the change in science and research dissemination. All of these drivers for open access are equally important for data and code as they represent the evidence which backs up a publication.

openaccess

Cartoon by Jorge Cham

Can we have open access without open data?

The answer is “No” according to Geoffrey Boulton (Royal Society, University of Edinburgh), Chair of the Working Group of the Science as an Open Enterprise report, who contended that publishing and data are invariably linked as data constitutes the evidence and maintains the self-correction and credibility in science: “Science corrects itself as long as you provide the knowledge by which it can do so”.
Brain Hole (Ubiquity Press) stressed that research needs an effective and efficient model of distribution and presented the model of publishing datasets in a similar way in which research is published – in peer-reviewed open access data journals. This model would create additional incentives for sharing data, as researchers would also gain citations and reputation by publicising their datasets.

Who owns the data?

Publishers sell the published research which was signed over to them by the very same research producers who are buying it.

Victoria Stodden (Columbia University, Open Economics Advisory Panel member) wrote in her blog how similar to the copyright sign-over to journals, many researchers are required to sign non-disclosure agreements when working with commercial data, even when no privacy issues are involved, preventing them from sharing it with other researchers. In some fields of science it goes even further, e.g. Ben Goldacre writes in Bad Pharma that “university administrators and ethics committees permit contracts with industry that explicitly say that the sponsor can control the data”, a research misconduct which is also one of the reasons for publication bias and overstating the benefits of treatments in medicines research.

How they can go together

Storing, linking and preserving data from social science research in a sustainable manner may be more complex than creating open access repositories for publications: after all researchers work sometimes with enormous datasets which can be usable by the research community only with proper descriptions of the research process in which the data was generated. After all even if some publishers or funders have data availability policies: these are rarely enforced, as making research data available would also require the establishment and maintenance of an elaborate data management infrastructures.

However, once open access infrastructures exist, it could be possible to have the data and code as one of the resources published along with the paper itself. Preserving these datasets on a large scale and in a sustainable manner would require massive repositories where datasets receive permanent digital identifiers, which would guarantee stable linking even if publishers or universities change the URLs.

While open access policies and structures might be getting more popular in some countries or science fields, there is still limited understanding of how to make data from research available on a wider scale. It is however clear that the experiences of the open access movement are key lessons for our understanding of how to make research data openly available.

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Dutch PhD-workshop on research design, open access and open data

- February 1, 2013 in Economic Publishing, EDaWaX, External Projects, Featured, Open Access, Open Data, Open Economics

This blog post is written by Esther Hoorn, Copyright Librarian, University of Groningen, the Netherlands.

If Roald Dahl were still alive, he would certainly be tempted to write a book about the Dutch social psychologist Diederik Stapel. For not only did he make up the research data to support his conclusions, but also he ate all the M&M’s, which he bought with public money for interviews with fictitious pupils in fictitious high schools. In the Netherlands the research fraud by Stapel was a catalyst to bring attention to the issue of research integrity and availability of research data. A new generation of researchers needs to be aware of the policy on sharing research data by the Dutch research funder NWO, the EU policy and the services of DANS, the Dutch Data archiving and networked services. In the near future, a data management plan will be required in every research proposal.

Verifiability

For some time now the library at the University of Groningen is organizing workshops for PhDs to raise awareness on the shift towards Open Access. Open Access and copyright are the main themes. The question also to address verifiability of research data came from SOM, the Research Institute of the Faculty of Economics and Business. The workshop is given as part of the course Research Design of the PhD program. The blogpost Research data management in economic journals proved to be very useful to get an overview of the related issues in this field.

Open Access

As we often see, Open Access was a new issue to most of the students. Because the library buys licenses the students don’t perceive a problem with access to research journals. Moreover, they are not aware of the big sums that the universities at present pay to finance access exclusively for their own staff and students. Once they understand the issue there is a strong interest. Some see a parallel with innovative distribution models for music. The PhDs come from all over the world. And more and more Open Access is addressed in every country of the world. One PhD from Indonesia mentioned that the Indonesian government requires his dissertation to be available through the national Open Access repository. Chinese students were surprised by availability of information on Open Access in China.

Assignment

The students prepared an assignment with some questions on Open Access and sharing research data. The first question still is on the impact factor of the journals in which they intend to publish. The questions brought the discussion to article level metrics and alternative ways to organize the peer review of Open Access journals.

Will availability of research data stimulate open access?

Example of the Open Access journal Economics

The blogpost Research data management in economic journals presents the results of the German project EdaWax, European Data Watch Extended. An important result of the survey points at the role of association and university presses. Especially it appears that many journals followed the data availability policy of the American Economic Association.

[quote] We found out that mainly university or association presses have high to very high percentages of journals owning data availability policies while the major scientific publishers stayed below 20%.

Out of the 29 journals with data availability policies, 10 used initially the data availability policy implemented by the American Economic Review (AER). These journals either used exactly the same policy or a slightly modified version.

For students it is assuring to see how associations take up their role to address this issue. An example of an Open Access journal that adopted the AER policy is Economics. And yes, this journal does have an impact factor in the Social Science Citation Index and also the possibility to archive the datasets in the Dataverse Network.

Re-use of research data for peer review

One of the students suggested that the public availability of research data (instead or merely research findings) may lead to innovative forms of review. This may facilitate a further shift towards Open Access. With access to underlying research data and methodologies used, scientists may be in a better position to evaluate the quality of the research conducted by peers. The typical quality label given by top and very good journals may then become less relevant, over time.
It was also discussed that journals may not publish a certain numbers of papers in a volume released e.g. four times a year, but rather as qualifying papers are available for publication throughout the year. Another point raised was that a substantial change in the existing publication mechanics will likely require either top journals or top business schools to lead the way, whereas associations of leading scientists in a certain field may also play an important role in such conversion.

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First Open Economics International Workshop Recap

- January 25, 2013 in Economic Publishing, Events, Featured, Open Access, Open Data, Open Economics, Open Research, Open Tools, Workshop

The first Open Economics International Workshop gathered 40 academic economists, data publishers and funders of economics research, researchers and practitioners to a two-day event at Emmanuel College in Cambridge, UK. The aim of the workshop was to build an understanding around the value of open data and open tools for the Economics profession and the obstacles to opening up information, as well as the role of greater openness of the academy. This event was organised by the Open Knowledge Foundation and the Centre for Intellectual Property and Information Law and was supported by the Alfred P. Sloan Foundation. Audio and slides are available at the event’s webpage.

Open Economics Workshop

Setting the Scene

The Setting the Scene session was about giving a bit of context to “Open Economics” in the knowledge society, seeing also examples from outside of the discipline and discussing reproducible research. Rufus Pollock (Open Knowledge Foundation) emphasised that there is necessary change and substantial potential for economics: 1) open “core” economic data outside the academy, 2) open as default for data in the academy, 3) a real growth in citizen economics and outside participation. Daniel Goroff (Alfred P. Sloan Foundation) drew attention to the work of the Alfred P. Sloan Foundation in emphasising the importance of knowledge and its use for making decisions and data and knowledge as a non-rival, non-excludable public good. Tim Hubbard (Wellcome Trust Sanger Institute) spoke about the potential of large-scale data collection around individuals for improving healthcare and how centralised global repositories work in the field of bioinformatics. Victoria Stodden (Columbia University / RunMyCode) stressed the importance of reproducibility for economic research and as an essential part of scientific methodology and presented the RunMyCode project.

Open Data in Economics

The Open Data in Economics session was chaired by Christian Zimmermann (Federal Reserve Bank of St. Louis / RePEc) and was about several projects and ideas from various institutions. The session examined examples of open data in Economics and sought to discover whether these examples are sustainable and can be implemented in other contexts: whether the right incentives exist. Paul David (Stanford University / SIEPR) characterised the open science system as a system which is better than any other in the rapid accumulation of reliable knowledge, whereas the proprietary systems are very good in extracting the rent from the existing knowledge. A balance between these two systems should be established so that they can work within the same organisational system since separately they are distinctly suboptimal. Johannes Kiess (World Bank) underlined that having the data available is often not enough: “It is really important to teach people how to understand these datasets: data journalists, NGOs, citizens, coders, etc.”. The World Bank has implemented projects to incentivise the use of the data and is helping countries to open up their data. For economists, he mentioned, having a valuable dataset to publish on is an important asset, there are therefore not sufficient incentives for sharing.

Eustáquio J. Reis (Institute of Applied Economic Research – Ipea) related his experience on establishing the Ipea statistical database and other projects for historical data series and data digitalisation in Brazil. He shared that the culture of the economics community is not a culture of collaboration where people willingly share or support and encourage data curation. Sven Vlaeminck (ZBW – Leibniz Information Centre for Economics) spoke about the EDaWaX project which conducted a study of the data-availability of economics journals and will establish publication-related data archive for an economics journal in Germany.

Legal, Cultural and other Barriers to Information Sharing in Economics

The session presented different impediments to the disclosure of data in economics from the perspective of two lawyers and two economists. Lionel Bently (University of Cambridge / CIPIL) drew attention to the fact that there is a whole range of different legal mechanism which operate to restrict the dissemination of information, yet on the other hand there is also a range of mechanism which help to make information available. Lionel questioned whether the open data standard would be always the optimal way to produce high quality economic research or whether there is also a place for modulated/intermediate positions where data is available only on conditions, or only in certain part or for certain forms of use. Mireille van Eechoud (Institute for Information Law) described the EU Public Sector Information Directive – the most generic document related to open government data and progress made for opening up information published by the government. Mireille also pointed out that legal norms have only limited value if you don’t have the internalised, cultural attitudes and structures in place that really make more access to information work.

David Newbery (University of Cambridge) presented an example from the electricity markets and insisted that for a good supply of data, informed demand is needed, coming from regulators who are charged to monitor markets, detect abuse, uphold fair competition and defend consumers. John Rust (Georgetown University) said that the government is an important provider of data which is otherwise too costly to collect, yet a number of issues exist including confidentiality, excessive bureaucratic caution and the public finance crisis. There are a lot of opportunities for research also in the private sector where some part of the data can be made available (redacting confidential information) and the public non-profit sector also can have a tremendous role as force to organise markets for the better, set standards and focus of targeted domains.

Current Data Deposits and Releases – Mandating Open Data?

The session was chaired by Daniel Goroff (Alfred P. Sloan Foundation) and brought together funders and publishers to discuss their role in requiring data from economic research to be publicly available and the importance of dissemination for publishing.

Albert Bravo-Biosca (NESTA) emphasised that mandating open data begins much earlier in the process where funders can encourage the collection of particular data by the government which is the basis for research and can also act as an intermediary for the release of open data by the private sector. Open data is interesting but it is even more interesting when it is appropriately linked and combined with other data and the there is a value in examples and case studies for demonstrating benefits. There should be however caution as opening up some data might result in less data being collected.

Toby Green (OECD Publishing) made a point of the different between posting and publishing, where making content available does not always mean that it would be accessible, discoverable, usable and understandable. In his view, the challenge is to build up an audience by putting content where people would find it, which is very costly as proper dissemination is expensive. Nancy Lutz (National Science Foundation) explained the scope and workings of the NSF and the data management plans required from all economists who are applying for funding. Creating and maintaining data infrastructure and compliance with the data management policy might eventually mean that there would be less funding for other economic research.

Trends of Greater Participation and Growing Horizons in Economics

Chris Taggart (OpenCorporates) chaired the session which introduced different ways of participating and using data, different audiences and contributors. He stressed that data is being collected in new ways and by different communities, that access to data can be an enormous privilege and can generate data gravities with very unequal access and power to make use of and to generate more data and sometimes analysis is being done in new and unexpected ways and by unexpected contributors. Michael McDonald (George Mason University) related how the highly politicised process of drawing up district lines in the U.S. (also called Gerrymandering) could be done in a much more transparent way through an open-source re-districting process with meaningful participation allowing for an open conversation about public policy. Michael also underlined the importance of common data formats and told a cautionary tale about a group of academics misusing open data with a political agenda to encourage a storyline that a candidate would win a particular state.

Hans-Peter Brunner (Asian Development Bank) shared a vision about how open data and open analysis can aid in decision-making about investments in infrastructure, connectivity and policy. Simulated models about investments can demonstrate different scenarios according to investment priorities and crowd-sourced ideas. Hans-Peter asked for feedback and input on how to make data and code available. Perry Walker (new economics foundation) spoke about the conversation and that a good conversation has to be designed as it usually doesn’t happen by accident. Rufus Pollock (Open Knowledge Foundation) concluded with examples about citizen economics and the growth of contributions from the wider public, particularly through volunteering computing and volunteer thinking as a way of getting engaged in research.

During two sessions, the workshop participants also worked on Statement on the Open Economics principles will be revised with further input from the community and will be made public on the second Open Economics workshop taking place on 11-12 June in Cambridge, MA.

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