Science Commons Symposium – Redmond 20th February

Science Commons
Image by dullhunk via Flickr

One of the great things about being invited to speak that people don’t often emphasise is that it gives you space and time to hear other people speak. And sometimes someone puts together a programme that means you just have to shift the rest of the world around to make sure you can get there. Lisa Green and Hope Leman have put together the biggest concentration of speakers in the Open Science space that I think I have ever seen for the Science Commons Symposium – Pacific Northwest to be held on the Microsoft Campus in Redmond on 20 February. If you are in the Seattle area and have an interest in the future of science, whether pro- or anti- the “open” movement, or just want to hear some great talks you should be there. If you can’t be there then watch out for the video stream.

Along with me you’ll get Jean-Claude Bradley, Antony Williams, Peter Murray-Rust, Heather Joseph, Stephen Friend, Peter Binfield, and John Wilbanks. Everything from policy to publication, software development to bench work, and from capturing the work of a single researcher to the challenges of placing several hundred millions dollars worth of drug discovery data into the public domain. All with a focus on how we make more science available and generate more and innovative. Not to be missed, in person or online – and if that sounds too much like self promotion then feel free to miss the first talk… ;-)

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Licenses and protocols for Open Science – the debate continues

This is an important discussion that has been going on in disparate places, but primarily at the moment is on the Open Science mailing list maintained by the OKF (see here for an archive of the relevant thread). To try and keep things together and because Yishay Mor asked, I thought I would try to summarize the current state of the debate.

The key aim here is to find a form of practice that will enhance data availability, and protect it into the future.

There is general agreement that there is a need for some sort of declaration associated with making data available. Clarity is important and the minimum here would be a clear statement of intention.Where there is disagreement is over what form this should take. Rufus Pollock started by giving the reasons why this should be a formal license. Rufus believes that a license provides certainty and clarity in a way that a protocol, statement of principles, or expression of community standards can not.  I, along with Bill Hooker and John Wilbanks [links are to posts on mailing list], expressed a concern that actually the use of legal language, and the notion of “ownership” of this by lawyers rather than scientists would have profound negative results. Andy Powell points out that this did not seem to occur either in the Open Source movement or with much of the open content community. But I believe he also hits the nail on the head with the possible reason:

I suppose the difference is that software space was already burdened with heavily protective licences and that the introduction of open licences was perceived as a step in the right direction, at least by those who like that kind of thing.         

Scientific data has a history of being assumed to be in public domain (see the lack of any license at PDB or Genbank or most other databases) so there isn’t the same sense of pushing back from an existing strong IP or licensing regime. However I think there is broad agreement that this protocol or statement would look a lot like a license and would aim to have the legal effect of at least providing clarity over the rights of users to copy, re-purpose, and fork the objects in question.

Michael Nielsen and John Wilbanks have expressed a concern about the potential for license proliferation and incompatibility. Michael cites the example of Apache, Mozilla, and GPL2 licenses. This feeds into the issue of the acceptability, or desirability of share-alike provisions which is an area of significant division. Heather Morrison raises the issue of dealing with commercial entities who may take data and use technical means to effectively take it out of the public domain, citing the takeover of OAIster by OCLC as a potential example.

This is a real area of contention I think because some of us (including me) would see this in quite a positive light (data being used effectively in a commercial setting is better than it not being used at all) as long as the data is still both legally and technically in the public domain. Indeed this is at the core of the power of a public domain declaration. The issue of finding the resources that support the preservation of research objects in the (accessible) public domain is a separate one but in my view if we don’t embrace the idea that money can and should be made off data placed in the public domain then we are going to be in big trouble sooner or later because the money will simply run out.

On the flip side of the argument is a strong tradition of arguing that viral licensing and share alike provisions protect the rights and personal investment of individuals and small players against larger commercial entities. Many of the people who support open data belong to this tradition, often for very good historical reasons. I personally don’t disagree with the argument on a logical level, but I think for scientific data we need to provide clear paths for commercial exploitation because using science to do useful things costs a lot of money. If you want people want to invest in using the outputs of publicly funded research you need to provide them with the certainty that they can legitimately use that data within their current business practice. I think it is also clear that those of us who take this line need to come up with a clear and convincing way of expressing this argument because it is at the centre of the objection to “protection” via licenses and share alike provisions.

Finally Yishay brings us back to the main point. Something to keep focussed on:

I may be off the mark, but I would argue that there’s a general principle to consider here. I hold that any data collected by public money should be made freely available to the public, for any use that contributes to the public good. Strikes me as a no-brainer, but of course – we have a long way to go. If we accept this principle, the licensing follows.         

Obviously I don’t agree with the last sentence – I would say that dedication to the public domain follows – but the principle I think is something we can agree that we are aiming for.

Travel plans

Michael Faraday delivering a Christmas Lecture in 1856.

Image via Wikipedia

For anyone who is interested I thought it might be helpful to say where I am going to be at meetings and conferences over the next few months. If anyone is going then drop me a line and we can meet up. Most of these are looking like interesting meetings so I recommend going to them if they are in your area (and in your area if you see what I mean) Continue reading “Travel plans”

Data is free or hidden – there is no middle ground

Science commons and other are organising a workshop on Open Science issues as a satellite meeting of the European Science Open Forum meeting in July. This is pitched as an opportunity to discuss issues around policy, funding, and social issues with an impact on the ‘Open Research Agenda’. In preparation for that meeting I wanted to continue to explore some of the conflicts that arise between wanting to make data freely available as soon as possible and the need to protect the interests of the researchers that have generated data and (perhaps) have a right to the benefits of exploiting that data.

John Cumbers proposed the idea of a ‘Protocol’ for open science that included the idea of a ‘use embargo’; the idea that when data is initially made available, no-one else should work on it for a specified period of time. I proposed more generally that people could ask that people leave data alone for any particular period of time, but that there ought to be an absolute limit on this type of embargo to prevent data being tied up. These kinds of ideas revolve around the need to forge community norms – standards of behaviour that are expected, and to some extent enforced, by a community. The problem is that these need to evolve naturally, rather than be imposed by committee. If there isn’t community buy in then proposed standards have no teeth.

An alternative approach to solving the problem is to adopt some sort ‘license’. A legal or contractual framework that creates obligation about how data can be used and re-used. This could impose embargoes of the type that John suggested, perhaps as flexible clauses in the license. One could imagine an ‘Open data – six month analysis embargo’ license. This is attractive because it apparently gives you control over what is done with your data while also allowing you to make it freely available. This is why people who first come to the table with an interest in sharing content always start with CC-BY-NC. They want everyone to have their content, but not to make money out of it. It is only later that people realise what other effects this restriction can have.

I had rejected the licensing approach because I thought it could only work in a walled garden, something which goes against my view of what open data is about. More recently John Wilbanks has written some wonderfully clear posts on the nature of the public domain, and the place of data in it, that make clear that it can’t even work in a walled garden. Because data is in the public domain, no contractual arrangement can protect your ability to exploit that data, it can only give you a legal right to punish someone who does something you haven’t agreed to. This has important consequences for the idea of Open Science licences and standards.

If we argue as an ‘Open Science Movement’ that data is in and must remain in the public domain then, if we believe this is in the common good, we should also argue for the widest possible interpretation of what is data. The results of an experiment, regardless of how clever its design might be, are a ‘fact of nature’, and therefore in the public domain (although not necessarily publically available). Therefore if any person has access to that data they can do whatever the like with it as long as they are not bound by a contractual arrangement. If someone breaks a contractual arrangement and makes the data freely available there is no way you can get that data back. You can punish the person who made it available if they broke a contract with you. But you can’t recover the data. The only way you can protect the right to exploit data is by keeping it secret. The is entirely different to creative content where if someone ignores or breaks licence terms then you can legally recover the content from anyone that has obtained it.

Why does this matter to the Open Science movement? Aren’t we all about making the data available for people to do whatever anyway? It matters because you can’t place any legal limitations on what people do with data you make available. You can’t put something up and say ‘you can only use this for X’ or ‘you can only use it after six months’ or even ‘you must attribute this data’. Even in a walled garden, once there is one hole, the entire edifice is gone. The only way we can protect the rights of those who generate data to benefit from exploiting it is through the hard work of developing and enforcing community norms that provide clear guidelines on what can be done. It’s that or simply keep the data secret.

What is important is that we are clear about this distinction between legal and ethical protections. We must not tell people that their data can be protected because essentially they can’t. And this is a real challenge to the ethos of open data because it means that our only absolutely reliable method for protecting people is by hiding data. Strong community norms will, and do, help but there is a need to be careful about how we encourage people to put data out there. And we need to be very strong in condemning people who do the ‘wrong’ thing. Which is why a discussion on what we believe is ‘right’ and ‘wrong’ behaviour is incredibly important. I hope that discussion kicks off in Barcelona and continues globally over the next few months. I know that not everyone can make the various meetings that are going on – but between them and the blogosphere and the ‘streamosphere‘ we have the tools, the expertise, and hopefully the will, to figure these things out.

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How do we build the science data commons? A proposal for a SciFoo session

Sign at The Googleplex.  Google limited access to Xenu.net, in March 2002.I realised the other day that I haven’t written an exciteable blog post about getting an invitation to SciFoo! The reason for this is that I got overexcited over on FriendFeed instead and haven’t really had time to get my head together to write something here. But in this post I want to propose a session and think through what the focus and aspects of that might be.

I am a passionate advocate of two things that I think are intimately related. I believe strongly in the need and benefits that will arise from building, using, and enabling the effective search and processing of a scientific data commons. I [1,2] and others (including John Wilbanks, Deepak Singh, and Plausible Accuracy) have written on this quite a lot recently. The second aspect is that I believe strongly in the need for effective useable and generic tools to record science as it happens and to process that record so that others can use it effectively. To me these two things are intimately related. By providing the tools that enable the record to be created and integrating them with the systems that will store and process the data commons we can enable scientists to record their work better, communicate it better, and make it available as a matter of course to other scientists (not necessarily immediately I should add, but when they are comfortable with it). Continue reading “How do we build the science data commons? A proposal for a SciFoo session”

Protocols for Open Science

interior detail, stata center, MIT. just outside science commons offices.

One of the strong messages that came back from the workshop we held at the BioSysBio meeting was that protocols and standards of behaviour were something that people would appreciate having available. There are many potential issues that are raised by the idea of a ‘charter’ or ‘protocol’ for open science but these are definitely things that are worth talking about. I thought I would through a few ideas out and see where they go. There are some potentially serious contradictions to be worked through. Continue reading “Protocols for Open Science”