Cameron Neylon

I spent two days this week visiting [Peter
Murray-Rust](http://wwmm.ch.cam.ac.uk/blogs/murrayrust) and others at
the [Unilever Centre for Molecular
Informatics](http://www-ucc.ch.cam.ac.uk/) at
[Cambridge](http://cam.ac.uk). There was a lot of useful discussion and
I learned an awful lot that requires more thinking and will no doubt
result in further posts. In this one I want to relay a conversation we
had over lunch with Peter, [Jim
Downing](http://wwmm.ch.cam.ac.uk/blogs/downing/), [Nico
Adams](//wwmm.ch.cam.ac.uk/blogs/adams/), Nick Day and [Rufus
Pollock](http://www.rufuspollock.org/) that seemed extremely productive.
It should be noted that what follows is my recollection so may not be
entirely accurate and shouldnâ€™t be taken to accurately represent other
peopleâ€™s views necessarily.

The appropriate way to license published scientific data is an argument
that has now been rolling on for some time. Broadly speaking the
argument has devolved into two camps. Firstly those who have a belief in
the value of share-alike or copyleft provisions of
[GPL](http://en.wikipedia.org/wiki/GNU_General_Public_License) and
similar licenses. Many of these people come from an [Open Source
Software](http://en.wikipedia.org/wiki/Open_source_software) or [Open
Content](http://en.wikipedia.org/wiki/Open_content) background. The
primary concern of this group is spreading the message and use of Open
Content and to prevent â€œfreeloadersâ€? from being able to use Open
material and not contribute back to the open community. A presumption in
this view is that a license is a good, or at least acceptable, way of
achieving both these goals. Also included here are those who think that
it is important to allow people the freedom to address their concerns
through copyleft approaches. I think it is fair to characterize Rufus as
falling into this latter group.

On the other side are those, including myself, who are concerned more
centrally with enabling re-use and re-purposing of data as far as is
possible. Most of us are scientists of one sort or another and not
programmers *per se*. We donâ€™t tend to be concerned about freeloading
(or in some cases welcome it as effective re-use). Another common
characteristic is that we have been prevented from being able to make
our own content as free as we would like due to copyleft provisions. I
prefer to make all my content CC-BY (or cc0 where possible). I am
frequently limited in my ability to do this by the wish to incorporate
CC-BY-SA or GFDL material. We are deeply worried by the potential for
licensing to make it harder to re-use and re-mix disparate sets of data
and content into new digital objects. There is a sense amongst this
group that "data is different" to other types of content, particulary in
its diversity of types and re-uses. More generally there is the concern
that anything that â€œsmells of lawyersâ€?, like something called a
â€œlicenseâ€?, will have scientists running screaming in the opposite
direction as they try to avoid any contact with their local
administration and legal teams.

What I think was productive about the discussion on Tuesday is that we
focused on what we could agree on with the aim of seeing whether it was
possible to find a common position statement on the limited area of best
practice for the publication of data that arises from public science. I
believe such a statement is important because there is a window of
opportunity to influence funder positions. Many funders are adopting
data sharing policies but most refer to â€œfollowing best practiceâ€?
and that best practice is thin on the ground in most areas. With funders
wielding the ultimate potential stick there is great potential to
bootstrap good practice by providing clear guidance and tools to make it
easy for researchers to deliver on their obligations. Funders in turn
will likely adopt this best practice as policy if it is widely accepted
by their research communities.

So we agreed on the following (I think â€" anyone should feel free to
correct me of course!):

1.  A simple statement is required along the forms ofÂ  â€œbest practice
    in data publishing is to apply protocol Xâ€?. Not a broad selection
    of licenses with different effects, not a complex statement about
    what the options are, but â€œbest practice is Xâ€?.
2.  The purpose of publishing public scientific data and collections of
    data, whether in the form of a paper, a patent, data publication, or
    deposition to a database, is to enable re-use and re-purposing of
    that data. Non-commercial terms prevent this in an unpredictable and
    unhelpful way. Share-alike and copyleft provisions have the
    potential to do the same under some circumstances.
3.  The scientific research community is governed by strong community
    norms, particularly with respect to attribution. If we could
    successfully expand these to include share-alike approaches as a
    community expectation that would obviate many concerns that people
    attempt to address via licensing.
4.  Explicit statements of the status of data are required and we need
    effective technical and legal infrastructure to make this easy for
    researchers.

So in aggregate I think we agreed a statement similar to the following:

"*Where a decision has been taken to publish data deriving from public
science research, best practice to enable the re-use and re-purposing of
that data, is to place it explicitly in the public domain via* {one of a
small set of protocols e.g. cc0 or PDDL}."

The advantage of this statement is that it focuses purely on what should
be done once a decision to publish has been made, leaving the issue of
what should be published to a separate policy statement. This also
sidesteps issues of which data should not be made public. It focuses on
data generated by public science, narrowing the field to the space in
which there is a moral obligation to make such data available to the
public that fund it. By describing this as best practice it also allows
deviations that may, for whatever reason, be justified by specific
people in specific circumstances. Ultimately the community, referees,
and funders will be the judge of those justifications. The [BBSRC data
sharing
policy](http://www.bbsrc.ac.uk/publications/policy/data_sharing_policy.html)
states for instance:

> BBSRC expects research data generated as a result of BBSRC support to
> be made available...no later than the release through
> publication...*in-line with established best practiceÂ  in the field*
> \[CN -- my emphasis\]...

The key point for me that came out of the discussion is perhaps that we
canâ€™t and wonâ€™t agree on a general solution for data but that we can
articulate best practice in specific domains. I think we have agreed
that for the specific domain of published data from public science there
is a way forward. If this is the case then it is a very useful step
forward.


I spent two days this week visiting Peter Murray-Rust and others at the Unilever Centre for Molecular Informatics at Cambridge. There was a lot of useful discussion and I learned an awful lot that requires more thinking and will no doubt result in further posts. In this one I want to relay a conversation we had over lunch with Peter, Jim Downing, Nico Adams, Nick Day and Rufus Pollock that seemed extremely productive.

A breakthrough on data licensing for public science?

The issue of licensing arrangements and best practice for making data
available has been brewing for some time but has just recently come to a
head. [John Wilbanks](http://scienceblogs.com/commonknowledge/) and
[Science Commons](http://sciencecommons.org/) have a reasonably well
established line that they have been developing for some time. [Michael
Nielsen](http://michaelnielsen.org/) has a [recent blog
post](http://michaelnielsen.org/blog/?p=540) and Rufus Pollock, of the
[Open Knowledge Foundation](http://www.okfn.org/), has also just
synthesised his thoughts in response into [a blog
essay](http://blog.okfn.org/2009/02/02/open-data-openness-and-licensing/).
I highly recommend reading John's [article on
licensing](http://precedings.nature.com/documents/1808/version/1) at
Nature Precedings, [Michael's blog
post](http://michaelnielsen.org/blog/?p=540), and [Rufus'
essay](http://blog.okfn.org/2009/02/02/open-data-openness-and-licensing/)
before proceeding. Another important document is the [discussion of the
license](http://www.stanford.edu/~vcs/papers/ERROLSI01092009.pdf) that
[Victoria Stodden](http://www.stanford.edu/~vcs/) is working to develop.
Actually if you've read them go and read them again anyway â€" it will
refresh the argument.

To crudely summarize, Rufus makes a cogent argument for the use of
explicit licenses applied to collections of data, and feels that
share-alike provisions in licenses or otherwise do not cause major
problems and that the benefit that arises from enforcing re-use
outweighs the problem. John's position is that it far better for
standards to be applied through social pressure ("community norms")
rather than licensing arrangements. He also believes that share-alike
provisions are bad because they break interoperability between different
types of objects and domains. One point that I think is very important
and (I think) is a point of agreement is that some form of license or at
dedication to the public domain will be crucial to developing best
practice. Even if the final outcome of debate is that everything will go
in the public domain it should be part of best practice to make that
explicit.

Broadly speaking I belong to John's camp but I don't want to argue that
case with this post. What is important in my view is that the debate
takes place and that we are clear about what the aims of that debate
are. What is it we are trying to achieve in the process of coming to
(hopefully) some consensus of what best practice should look like?  
It is important to remember that anyone can assert a license (or lack
thereof) on any object that they (assert they) own or have rights over.
We will never be able to impose a specific protocol on all researchers,
all funders. Therefore what we are looking for is not the perfect
arrangement but a balance between what is desired, what can be
practically achieved, and what is politically feasible. We do need a
coherent consensus view that can be presented to research communities
and research funders. That is why the debate is important. We also need
something that works, and is extensible into the future, where it will
stand up to the development of new types of research, new types of data,
new ways of making that data available, and perhaps new types of
researchers altogether.

I think we agree that the minimal aim is to enable, encourage, and
protect into the future the ability to re-use and re-purpose the
publicly published products of publicly funded research. Arguments about
personal or commercial work are much harder and much more subtle.
Restricting the argument to publicly funded researchers makes it
possible to open a discussion with a defined number of funders who have
a public service and public engagement agenda. It also makes the moral
arguments much clearer.

In focussing on research that is being made public we short circuit the
contentious issue of timing. The right, or the responsibility, to
commercially exploit research outputs and the limitations this can place
on data availability is a complex and difficult area and one in which
agreement is unlikely any time soon. I would also avoid the word
â€œOpenâ€?. This is becoming a badly overloaded term with both political
and emotional overtones, positive and negative. Focussing on what should
happen *after* the decision has been to go public reduces the argument
to â€œwhat is best practice for making research outputs availableâ€?.
The question of when to make them available can then be kept separate.
The key question for the current debate is not *when* but *how*.

So what I believe the debate should be about is the establishment, if
possible, of a consensusÂ  protocol or standard or license for enabling
and ensuring the availability of the research outputs associated with
publicly published, publicly funded research.Â  Along side this is the
question of establishing mechanisms, for researchers to implement and be
supported to observe these standards, as well as for â€œenforcementâ€?.
These might be trademarks, community standards, or legal or contractual
approaches as well as systems and software to make all of this work,
including trackbacks, citation aggregators, and effective data
repositories. In addition we need to consider the public relations issue
of selling such standards to disparate research funders and research
communities.

Perhaps a good starting point would be to pinpoint the issues where
there is general agreement and map around those. If we agree some
central principles then we can take an empirical approach to the
mechanisms. We're scientists after all aren't we?


The issue of licensing arrangements and best practice for making data available has been brewing for some time but has just recently come to a head. John Wilbanks and Science Commons have a reasonably well established line that they have been developing for some time. Michael Nielsen has a recent blog post and Rufus Pollock, of the Open Knowledge Foundation, has also just synthesised his thoughts in response into a blog essay.

Rogue Scholar Beiträge

A breakthrough on data licensing for public science?

Best practice for data availability â€“ the debate starts…well over there really