Cameron Neylon

There has been a lot of recent discussion about the relative importance
of Open Source and Open Data
([Friendfeed](http://friendfeed.com/e/4a8c5012-ee18-2b72-390a-ca3298b3a57c/open-data-is-more-important-than-open/),
[Egon
Willighagen](http://chem-bla-ics.blogspot.com/2009/03/open-data-versus-capatalism.html),
[Ian
Davis](http://www.google.co.uk/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fiandavis.com%2Fblog%2F2009%2F03%2Fopen-data-open-source&ei=aPfUSd7GEaWsjAfA8ZnrDg&usg=AFQjCNF--83L-d02v50DIzj8h6mV4q__pg&sig2=jIUzMqWW5glEKHwbL4148w)).
I don't fancy recapitulating the whole argument but following a
discussion on Twitter with [Glyn Moody](http://twitter.com/glynmoody)
this morning \[[1](http://twitter.com/glynmoody/statuses/1437524981),
[2](http://twitter.com/CameronNeylon/status/1437541770),
[3](http://twitter.com/glynmoody/statuses/1437548842),
[4](http://twitter.com/CameronNeylon/status/1437558740),
[5](http://twitter.com/CameronNeylon/status/1437563815),
[6](http://twitter.com/glynmoody/statuses/1437575352),
[7](http://twitter.com/glynmoody/statuses/1437662765),
[8](http://twitter.com/CameronNeylon/status/1437727643)\] I think there
is a way of looking at this with a slightly different perspective. But
first a short digression.

I attended a [workshop late last year on Open
Science](http://www.okfn.org/wiki/OpenScience/Workshop) run by the [Open
Knowledge Foundation](http://www.okfn.org). I spent a significant part
of the time arguing with Rufus Pollock about data licences, an argument
that is still going on. One of Rufus' challenges to me was to commit to
working towards using only Open Source software. His argument was that
there wasn't really any excuses any more. [Open
Office](http://www.openoffice.org/) could do the job of [MS
Office](http://office.microsoft.com/en-us/default.aspx),
[Python](http://python.org) with [SciPy](http://scipy.org) was up to the
same level as [MatLab](http://en.wikipedia.org/wiki/MATLAB), and
anything specialist needed to be written anyway so should be open source
from the off.

I took this to heart and I have tried, I really have tried. I needed a
new computer and, although I got a Mac (not really ready for Linux yet),
I loaded it up with Open Office, I haven't yet put my favourite data
analysis package on the computer
([Igor](http://www.wavemetrics.com/products/IGORPro/igorpro.htm) if you
must know), and have been working in Python to [try to get some stuff up
to speed](http://github.com/cameronneylon/sas/tree/master). But I have
to ask whether this is the best use of my time. As is often the case
with my arguments this is a return on investment question. I am paid by
the taxpayer to do a job. At what point is the extra effort I am putting
into learning to use, or in some cases fight with, new tools cost more
than the benefit that is gained, by making my outputs freely available?

Sometimes the problems are imposed from outside. I spent a good part of
yesterday battling with an appalling, password protected,
macroed-to-the-eyeballs Excel document that was the required format for
me to fill in a form for an application. The file crashed Open Office
and only barely functioned in Mac Excel at all. Yet it was required, in
that format, before I could complete the application. Sometimes the
software is just not up to scratch. Open Office Writer is fine, but the
presentation and spreadsheet modules are, to be honest, a bit ropey
compared to the commercial competitors. And with a Mac I now have
Keynote which is just so vastly superior that I have now transferred
wholesale to that. And sometimes it is just a question of time. Is it
really worth me learning Python to do data analysis that I could knock
in Igor in a tenth of the time?

In this case the answer is, probably yes. Because it means I can do more
with it. There is the potential to build something that logs process the
way I want to , the potential to convert it to run as a web service. I
could do these things with other OSS projects as well in a way that I
can't with a closed product. And even better because there is a big open
community I can ask for help when I run into
[problems](http://statingthebleedingobvious.wordpress.com/2009/03/16/problems-with-creating-a-new-matplotlib-scalebase-class/).

It is easy to lose sight of the fact that for most researchers software
is a means to an end. For the Open Researcher what is important is the
ability to reproduce results, to criticize and to examine. Ideally this
would include every step of the process, including the software. But for
most issues you don't need, or even want, to be replicating the work
right down to the metal. You wouldn't after all expect a researcher to
be forced to run their software on an open source computer, with an open
source chipset. You aren't necessarily worried what operating system
they are running. What you are worried about is whether it is possible
read their data files and reproduce their analysis. If I take this just
one step further, it doesn't matter if the analysis is done in MatLab or
Excel, as long as the files are readable in Open Office and the analysis
is described in sufficient detail that it can be reproduced or
re-implemented.

Lets be clear about this: it would be better if the analysis were done
in an OSS environment. If you have the option to work in an OSS
environment you can also save yourself time and effort in describing the
process and others have a much better chances of identifying the sources
of problems. It is not good enough to just generate an Excel file, you
have to generate an Excel file that is readable by other software (and
here I am looking at the increasing number of instrument manufacturers
providing software that generates so called Excel files that often
aren't even readable in Excel). In many cases it might be easier to work
with OSS so as to make it easier to generate an appropriate file. But
there is another important point; if OSS generates a file type that is
undocumented or worse, obfuscated, then that is also unacceptable.

Open Data is crucial to Open Research. If we don't have the data we have
nothing to discuss. Open Process is crucial to Open Research. If we
don't understand how something has been produced, or we can't reproduce
it, then it is worthless. Open Source is not necessary, but, if it is
done properly, it can come close to being sufficient to satisfy the
other two requirements. However it can't do that without Open Standards
supporting it for documenting both file types and the software that uses
them.

The point that came out of the conversation with Glyn Moody for me was
that it may be more productive to focus on our ability to re-implement
rather than to simply replicate. Re-implementability, while an awful
word, is closer to what we mean by replication in the experimental world
anyway. Open Source is probably the best way to do this in the long
term, and in a perfect world the software and support would be there to
make this possible, but until we get there, for many researchers, it is
a better use of their time, and the taxpayer's money that pays for that
time, to do that line fitting in Excel. And the damage is minimal as
long as source data and parameters for the fit are made public. If we
push forward on all three fronts, Open Data, Open Process, and Open
Source then I think we will get there eventually because it is a more
effective way of doing research, but in the meantime, sometimes, in the
bigger picture, I think a shortcut should be acceptable.


There has been a lot of recent discussion about the relative importance of Open Source and Open Data (Friendfeed, Egon Willighagen, Ian Davis). I don’t fancy recapitulating the whole argument but following a discussion on Twitter with Glyn Moody this morning [1, 2, 3, 4, 5, 6, 7, 8] I think there is a way of looking at this with a slightly different perspective. But first a short digression.

Open Data, Open Source, Open Process: Open Research

*The second installment of the paper ([first part
here](http://cameronneylon.net/blog/a-personal-view-of-open-science-part-i/))
where I discuss building tools for Open (or indeed any) Science.*

**Tools for open science -- building around the needs of scientists**

It is the rapid expansion and development of tools that are loosely
categorised under the banner of 'Web2.0' or 'Read-write web' that makes
the sharing of research material available. Many of the generic tools,
particularly those that provide general document authoring capabilities,
have been adopted and used by a wide range of researchers. Online office
tools can enable collaborative development of papers and proposals
without the need for emailing documents to multiple recipients and the
resultant headaches associated with which version is which. Storing
spreadsheets, databases, or data online means that collaborators have
easy access to the most recent versions and can see how these are
changing. More generally the use of RSS feed readers and bookmarking
sites to share papers of interest and, to some extent, to distribute the
task of triaging the literature are catching in in some communities. The
use of microblogging platforms such as Twitter and aggregation and
conversational tools such as Friendfeed have recently been used very
effectively to provide coverage of conferences in progress, including
collaborative note-taking. In combination with streamed or recorded
video as well as screencasts and sharing of presentations online the
idea of a dstributed conference, while not an everyday reality, is
becoming feasible.

However it is often the case that,while useful, generic web based
services do not provide desired functionality or do not fit well into
the existing workflows of researchers. Here there is the opportunity,
and sometime necessity, to build specialised or adapated tools.
Collaborative preparation of papers is a good example of this.
Conventional web bookmarking services, such as del.icio.us provide a
great way of sharing the literature or resources that a paper builds on
with other authors but they do not automatically capture and recognise
the necessary metadata associated with published papers (journal, date,
author, volume, page numbers). Specialised services such as citeulke and
Connotea have been developed to enable one click bookmarking of
published literature and these have been used effectively by for example
using a specific tag for references associated with a specific paper in
progress. The problem with these services as they exist at the moment is
that they don't provide the crucial element in the workflow that
scientists want to aggregate the references for, the formatting of the
references in the finalised paper. Indeed the lack of formatting
functionality in GoogleDocs, the most widely used collaborative writing
tool, means that in practice the finalised document is usually cut and
pasted into Word and the references formatted using proprietary software
such as Endnote.The available tools do not provide the required
functionality.

A number of groups and organisations have investigated the use of Blogs
and Wikis as collaborative and shareable laboratory notebooks. However
few of these systems offer good functionality 'out of the box'. While
there are many electronic laboratory notebook systems sold by commercial
interests most are actually designed around securing data rather than
sharing it so are not of interesthere. While the group of Jean-Claude
Bradley has used the freely hosted WikiSpaces as a [laboratory
notebook](http://usefulchem.wikispaces.com) without further
modification, much of the data and analysis is hosted on other services,
including YouTube, FlickR, and GoogleDocs. The OpenWetWare group has
made extensive modifications to the MediaWiki system to [provide
laboratory notebook
functionality](http://openwetware.org/wiki/Lab_Notebook) whereas Garret
Lisi has adapted the TiddlyWiki framework as a way of [presenting his
notebook](http://deferentialgeometry.org). The [Chemtools
collaboration](http://chemtools.chem.soton.ac.uk/) at the University of
Southampton has developed a specialised Blog platform . Commercial
offerings in the area of web based lab notebooks are also starting to
appear. All of these different systems have developed because of the
specialised needs of recording the laboratory work of the scientists
they were designed for. The different systems make different assumptions
about where they fit in the workflow of the research scientist, and what
that workflow looks like. They are all, however, built around the idea
that they need to satisfy the needs of the user.

This creates a tension in tool building. General tools, that can be used
across a range of disciplines, are extremely challenging to design,
because workflows, and the perception of how they work, are different in
different disciplines. Specialist tools can be built for specific fields
but often struggle to translate into new areas. Because the market is
small in any field the natural desire for designers is to make tools as
general as possible. However in the process of trying to build for a
sufficiently general workflow it is often the case that applicability to
specific workflows is lost. There is a strong argument based on this for
building interoperable modules, rather than complete systems, that will
allow domain specialists to stich together specific solutions for
specific fields or even specific experiments. Interoperability of
systems and standards that enable it is a criteria that is sometimes
lost in the development process, but is absolutely essential to making
tools and processes shareable. The use of workflow management tools,
such as [Taverna](http://en.wikipedia.org/wiki/Taverna_workbench),
[Kepler](http://en.wikipedia.org/wiki/Kepler_scientific_workflow_system),
and [VisTrails](http://www.vistrails.org/index.php/Main_Page) have an
important role to play here.

While not yet at a stage where they are widely configurable by end users
the vision behind them has the potential both to make data analysis much
more straightforward for experimental scientist but also to solve many
of the problems involved in sharing process, as opposed to data. The
idea of visually wiring up online or local analysis tools to enable data
processing pipelines is compelling. The reason most experimental
scientists use spreadsheets for data analysis is that they do not wish
to learn programming languages. Providing visual programming tools along
with services with clearly defined inputs and outputs will make it
possible for a much wider range of scientists to use more sophisticated
and poweful analysis tools. What is more the ability to share, version,
and attribute, workflows will go some significant distance towards
solving the problem of sharing process. Services like
[MyExperiment](http://myexperiment.org) which provide an environment for
sharing and versioning Taverna workflows provide a natural way of
sharing the details of exactly how a specific analysis is carried out.
Along with an electronic notebook to record each specific use of a given
workflow or analysis procedure (which can be achieved automatically
though an API) the full details of the raw data, analysis procedure, and
any specific parameters used, can be recorded. This combination offers a
potential route out of the serious problem of sharing research processes
if the appropriate support infrastructure can be built up.

Also critical to successful sharing is a shared language or vocabulary.
The development of ontologies, controlled vocabularies, and design
standards are all important in sharing knowledge and crucial to
achieving the ulitmate goals of making this knowledge machine readable.
While there are divisions in the technical development and user
communities over the development and use of controlled vocabularies
there is little disagreement over the fact that good vocabularies
combined with good tools are useful. The disagreements tend to lie in
how they are best developed, when they should be applied, and whether
they are superior to or complementary to other approaches such as text
mining and social tagging. An integrated and mixed approach to the use
of controlled vocabularies and standards is the most likely to be
successful. In particular it is important to match the degree of
structure in the description to the natural degree of structure in the
object or objects being described. Highly structured and consistent data
types, such as crystal structures and DNA sequences, can benefit greatly
from highly structured descriptions which are relatively straightforward
to create, and in many cases are the standard outputs of an analysis
process. For large scale experimental efforts the scale of the data and
sample management problem makes an investment in detailed and structured
desriptions worth while. In a small laboratory doing unique work,
however, there may be a strong case for using local descriptions and
vocabularies that are less rigorous but easier to apply and able to grow
to fit the changing situation on the ground. Ideally designed in such a
way that mapping onto an external vocabulary is feasible if it is
required or useful in the future.

Making all of this work requires that researchers adopt these tools and
that a community develops that is big enough to provide the added value
that these tools might deliver. For a broad enough community to adopt
these approaches the tools must fit well in their existing workflow and
help to deliver the things that researchers are already motivated to
produce. For most researchers, published papers are the measure of their
career success and the basis of their reward structures. Therefore tools
that make it easier to write papers, or that help researchers to write
better papers, are likely to get traction. As the expectations of the
quality and completeness of supporting data increase for published
papers, tools that make it easier for the researcher to collate and
curate the record of their research will become important. It is the
process of linking the record of what happened in the laboratory, or
study, to the first pass intepretation and analysis of data, through
further rounds of analysis until a completed version is submitted for
review, that is currently poorly supported by available tools, and it is
this need that will drive the development of improved tools. These tools
will enable the disparate elements of the record of research, currently
scattered between paper notebooks, various data files on multiple hard
drives, and unconnected electronic documents, to be chained together.
Once this record is primarily electronic, and probably stored online in
a web based system, the choice to make the record public at any stage
from the moment the record is made to the point of publication, will be
available. The reason to link this to publication is to tie it into an
existing workflow in the first instance. Once the idea is embedded the
steps involved in making the record even more open are easily taken.

*[Part
III](http://cameronneylon.net/blog/a-personal-view-of-open-science-part-iii-social-issues/)
covers social issues around Open Science.*


The second installment of the paper (first part here) where I discuss building tools for Open (or indeed any) Science.


 Tools for open science – building around the needs of scientists

It is the rapid expansion and development of tools that are loosely categorised under the banner of ‘Web2.0’ or ‘Read-write web’ that makes the sharing of research material available.

A personal view of Open Science &#8211; Part II &#8211; Tools

On Monday 1 September we had a one day workshop in Southampton
discussing the issues that surround 'Open Science'. This was very free
form and informal and I had the explicit aim of getting a range of
people with different perspectives into the room to discuss a wide range
of issues, including tool development, the social and career structure
issues, as well as ideas about standards and finally, what concrete
actions could actually be taken. You can find live blogging and other
commentary in the associated [Friendfeed
room](http://friendfeed.com/rooms/soton-open-science-workshop-1-9-08)
and information on who attended as well as links to many of the
presentations on the [conference
wiki](http://sotonopensciworkshop.wikispaces.com/).

Broadly speaking the day was divided into three chunks, the first was
focussed on tools and services and included presentations on
[MyExperiment](http://myexperiment.org),
[Mendeley](http://www.mendeley.com/),
[Chemtools](http://chemtools.chem.soton.ac.uk/), and [Inkspot
Science](http://www.inkspotscience.com/). Branwen Hide of Research
Information Network has written [more on this
part](http://www.rin.ac.uk/node/440). Given that the room contained more
than the usual suspects the conversation focussed on usability and
interfaces rather than technical aspects although there was a fair bit
of that as well.

The second portion of the day revolved more around social challenges and
issues. [Richard Grant](http://network.nature.com/people/rpg/blog/)
presented his experience of blogging on an official university
sanctioned site and the value of that for both outreach and education.
One point he made was that the 'lack of adoption problem' seen in
science just doesn't seem to exist in the humanities. Perhaps this is
because scientists don't generally see 'writing' as a valuable thing in
its own right. Certainly there is a preponderance of scientists who
happen also to see themselves as writers on [Nature
Network](http://network.nature.com).

[Jennifer Rohn](http://network.nature.com/people/UE19877E8/blog)
followed on from Richard, and objected to my characterising her
presentation as "the skeptic's view". A more accurate characterisation
would have been "I'd love to be open but at the moment I can't: This is
what has to change to make it work". She presented a great summary of
the proble, particularly from the biological scientist's point of view
as well as potential solutions. Essentially the problem is that of the
'Minimum Publishable Unit' or research quantum as well as what 'counts'
as publication. Her main point was that for people to be prepared to
publish material that falls short of a full paper they need to get some
proportional credit for that. This folds closely into the discussion of
what can be cited and what should be cited in particular contexts. I
have used the phrase 'data sized peg into a paper shaped hole' to
describe this in the past.

After lunch [Liz Lyon](http://www.ukoln.ac.uk/ukoln/staff/e.j.lyon/)
from [UKOLN](http://www.ukoln.ac.uk/) talked about curation and long
term archival storage which lead into an interesting discussion about
the archiving of blogs and other material. Is it worth keeping? One
answer to this was to look at the real interest today in diaries from
the second world war and earlier from 'normal people'. You don't
necessarily need to be a great scientist, or even a great blogger, for
the material to be of potential interest to historians in 50-100 years
time. But doing this properly is hard -- in the same way that
maintaining and indexing data is hard. Disparate sites, file formats,
places of storage, and in the end whose blog is it actually?
Particularly if you are blogging for, or recording work done at, a
research institution.

The final session was about standards or 'brands'. Yaroslav Nikolaev
talked about semantic representations of experiments. While important it
was probably a shame in the end we did this at the end of the day
because it would have been helpful to get more of the non-techie people
into that discussion to iron out both the communication issues around
semantic web as well as describing the real potential benefits. This
remains a serious gap -- the experimental scientists who could really
use semantic tools don't really get the point, and the people developing
the tools don't communicate well what the benefits are, or in some cases
(not all I hasten to add!) actually build the tools the experimentalists
want.

I talked about the possibility of a 'certificate' or standard for Open
Science, and the idea of an organisation to police this. It would be
safe to say that, while people agreed that clear definitions would be
hepful, the enhusiasm level for a standards organisation was pretty much
zero. There are more fundamental issues of actually building up enough
examples of good practice, and working towards identifying best practice
in open science, that need to be dealt with before we can really talk
about standards.

On the other hand the idea of 'the fully supported' paper got immediate
and enthusiastic support. The idea here is deceptively simple, and has
been discussed elsewhere; simply that all the relevant supporting
information for a paper (data, detailed methodology, software tools,
parameters, database versions etc. as well as access to required
materials at reasonable cost) should be available for any published
paper. The challenge here lies in actually recording experiments in such
a way that this information can be provided. But if all of the record is
available in this form then it can be made available whenever the
researcher chooses. Thus by providing the tools that enable the fully
supported paper you are also providing tools that enable open science.

Finally we discussed what we could actually do: [Jean-Claude
Bradley](http://usefulchem.blogspot.com) discussed the idea of an [Open
Notebook Science challenge](http://onschallenge.wikispaces.com/) to
raise the profile of ONS (this is now setup -- more on this to follow).
Essentially a competition type approach where individuals or groups can
contribute to a larger scientific problem by collecting data -- where
the teams get judged on how well they describe what they have done and
how quickly they make it available.

The most specific action proposed was to draft a 'Letter to Nature'
proposing the idea of the fully supported paper as a submission
standard. The idea would be to get a large number of high profile
signatories on a document which describesÂ  a concrete step by step plan
to work towards the final goal, and to send that as correspondence to a
high profile journal. I have been having some discussions about how to
frame such a document and hope to be getting a draft up for discussion
reasonably soon.

Overall there was much enthusiasm for things Open and a sense that many
elements of the puzzle are falling into place. What is missing is
effective coordinated action, communication across the whole community
of interested and sympathetic scientsts, and critically the high profile
success stories that will start to shift opinion. These ought to, in my
opinion, be the targets for the next 6-12 months.


On Monday 1 September we had a one day workshop in Southampton discussing the issues that surround ‘Open Science’. This was very free form and informal and I had the explicit aim of getting a range of people with different perspectives into the room to discuss a wide range of issues, including tool development, the social and career structure issues, as well as ideas about standards and finally, what concrete actions could actually be taken.

The Southampton Open Science Workshop &#8211; a brief report

So a bit of a first for me. I can vaguely claim to have contributed to
two things into the print version of [*Nature* this
week](http://www.nature.com/nature/journal/v455/n7211/). Strictly
speaking my involvement in the first, the '[From the
Blogosphere](http://network.nature.com/people/maxine/blog/2008/09/18/blogging-challenge-to-senior-scientists-18-september-2008)'
piece on the [Science Blogging
Challenge](http://blogs.nature.com/wp/nascent/2008/09/science_blogging_challenge.html),
was really restricted to discussing the idea (originally from [Richard
Grant](http://network.nature.com/people/rpg/blog) I believe) and now a
bit of cheerleading and ultimately some judging. The second item though
I can claim some credit for in as much as it is a [Q&A with myself and
Jean-Claude
Bradley](http://www.nature.com/news/2008/080915/full/455273a.html) that
was done when we visited Nature Publishing Group in London a few weeks
back.

It is great that a journal like *Nature* views the ideas of data
publication, [open notebook
science](http://drexel-coas-elearning.blogspot.com/2006/09/open-notebook-science.html),
and open science in general as worthy of featuring. This is not an
isolated instance either, as we can point to the good work of the Web
Publishing Group, in developing useful resources such as [*Nature
Precedings*](http://precedings.nature.com), as well as previous features
in the print edition such as the [Horizons
article](http://www.nature.com/nature/journal/v451/n7179/full/451648a.html)
(there is also [another
version](http://precedings.nature.com/documents/1200/version/1) on
Nature Precedings) written by [Peter
Murray-Rust](http://wwmm.ch.cam.ac.uk/blogs/murrayrust/). One thing I
have heard said many times in recent months is that while people who
advocate open science may not agree with everything NPG with respect to
copyright and access, people are impressed and encouraged by the degree
of engagement that they maintain with the community.

I did however just want to clarify one or two of the things I apparently
said. I am not claiming that I didn't say those things -- the interview
was recorded after all -- but just that on paper they don't really quite
match what I think I meant to say. Quoting from the article:

> CN-Most publishers regard what we do as the equivalent of presenting
> at a conference, or a preprint. That hasn't been tested across a wide
> range of publishers, and there's at least one â€" the American
> Chemical Society â€" that doesn't allow prepublication in any form
> whatsoever.

That sounds a little more extreme than what I meant to say -- there are
a number of publishers that don't allow submission of material that has
appeared online as a pre-print and the ACS has said that they regard
online publication as equivalent to a pre-print. I don't have any
particular sympathy for the ACS but I think they probably do allow
publication of material that was presented at ACS conferences.

> CN-Open notebooks are practical but tough at the moment. My feeling is
> that the tools are not yet easy enough to use. But I would say that a
> larger proportion of people will be publishing electronically and
> openly in ten years.

Here I think what I said is too conservative on one point and possibly
not conservative enough on the other. I did put my neck out and say that
I think the *majority* of scientists will be using electronic lab
notebooks of one sort or another in ten years. Funder data sharing
policies will drive a much greater volume of material online post
publication (hopefully with higher quality description) and this may
become the majority of all research data. I think that more people will
be making more material available openly as it is produced as well but I
doubt that this will be a majority of people in ten years -- I hope for
a sizeable and significant minority and that's what we will continue to
work towards.


So a bit of a first for me. I can vaguely claim to have contributed to two things into the print version of

 Nature

this week. Strictly speaking my involvement in the first, the ‘From the Blogosphere‘ piece on the Science Blogging Challenge, was really restricted to discussing the idea (originally from Richard Grant I believe) and now a bit of cheerleading and ultimately some judging.

Q&#38;A in this week&#8217;s Nature &#8211; one or two (minor) clarifications

So [Michael Nielsen](http://www.michaelnielsen.org/), one morning at
breakfast at Scifoo asked one of those questions which never has a short
answer; â€˜So how did you get into this open science thing?â€™ and I
realised that although I have told the story to many people I havenâ€™t
ever written it down. Perhaps this is a meme worth exploring more
generally but I thought others might be interested in my story, partly
because it illustrates how funding drives scientists, and partly because
it shows how the combination of opportunism and serendipity can make for
successful bedfellows.

In late 2004 I was spending a lot of my time on the management of a
large collaborative research project and had had a run of my own grant
proposals rejected. I had a student interested in doing a PhD but no
direct access to funds to support the consumables cost of the proposed
project. [Jeremy
Frey](http://www.soton.ac.uk/~jgfchem/users.php?user=15) had been on at
me for a while to look at implementing the electronic lab notebook
system that he had lead the development of and at the critical moment he
pointed out to me a special call from the
[BBSRC](http://www.bbsrc.ac.uk) for small projects to prototype,
develop, or implement e-science technologies in the biological sciences.
It was a light touch review process and a relatively short application.
More to the point it was a way of funding some consumables.

So the grant was written. I wrote the majority of it, which makes
somewhat interesting reading in retrospect. I didnâ€™t really know what
I was talking about at the time (which seems to be a theme with my
successful grants). The original plan was to use the existing, fully
semantic, [rdf backed electronic lab notebook](http://mytea.org.uk/) and
develop models for use in a standard biochemistry lab. We would then
develop systems to enable a relational database to be extracted from the
rdf representation and present this on the web.

The grant was successful but the start was delayed due to shenanigans
over the studentship that was going to support the grant and the
movement of some of the large project to another institution with one of
the investigators. Partly due to the resulting mess I applied for the
job I ultimately accepted at RAL and after some negotiation organised an
80:20 split between RAL and Southampton.

By the time we had a student in place and had got the grant started it
was clear that the existing semantic ELN was not in a state that would
enable us to implement new models for our experiments. However at this
stage there was a blog system that had been developed in Jeremyâ€™s
group and it was thought it would be an interesting experiment to use
this as a notebook. This would be almost the precise opposite of the rdf
backed ELN. Looking back at it now I would describe it as taking the
opportunity to look at a Web 2.0 approach to the notebook as compared to
a Web 3.0 approach but bear in mind that at the time I had little or no
idea of what these terms meant, let alone the care with which they need
to be used.

The blog based system was great for me as it meant I could follow the
studentâ€™s work online and doing this I gradually became aware of blogs
in general and the use of feed readers. The RSS feed of the LaBLog was a
great help as it made following the details of experiments remotely
straightforward. This was important as by now I was spending three or
four days a week at RAL while the student was based in Southampton. As
we started to use the blog, at first in a very naÃ¯ve way we found
problems and issues which ultimately led to us thinking about and
designing the organisational approach I have written about elsewhere
\[[1](http://blog.openwetware.org/scienceintheopen/2007/08/17/the-southampton-e-lab-blog-notebook-part-2-eln-strategy/),
[2](http://blog.openwetware.org/scienceintheopen/2007/08/20/the-southampton-e-lab-blog-notebook-part-3-implementation/)\].
By this stage I had started to look at other services online and was
playing around with [OpenWetWare](http://openwetware.org) and a few
other services, becoming vaguely aware of [Creative
Commons](http://creativecommons.org) licenses and getting a grip on the
Web 2.0 versus Web 3.0 debate.

To implement our newly designed approach to organising the LaBLog we
decided the student would start afresh with a clean slate in a new blog.
By this stage I was playing with using the blog for other things and had
started to discover that there were issues that meant the ID
authentication we were using didnâ€™t always work through the RAL
firewall. I ended up having complicated VPN setups, particularly working
from home, where I couldnâ€™t log on to the blog and I have my email
online at the same time. This, obviously, was a pain and as we were
moving to a new blog which could have new security settings I said,
â€˜stuff it, letâ€™s just make it completely visible and be done with
itâ€™.

So there you go. The critical decision to move to an Open Notebook
status was taken as the result of a firewall. So serendipity, or at
least the effect of outside pressures, was what made it happen.Â  I
would like to say it was a carefully thought out philosophical decision
but, although the fact that I was aware of the open access movement,
creative commons, OpenWetWare, and others no doubt prepared the
background that led me to think down that route, it was essentially the
result of frustration.

So, so far, opportunism and serendipity, which brings us back to
opportunism again, or at least seizing an opportunity. Having made the
decision to â€˜go openâ€™ two things clicked in my mind. Firstly the
fact that this was rather radical. Secondly, the fact that all of these
Web 2.0 tools combined with an open approach could lead to a marked
improvement in the efficiency of collaborative science, a kind of
â€˜Science 2.0â€™ \[yes, I know, donâ€™t laugh, this would have been
around March 2007\]. Here was an opportunity to get my name on a really
novel and revolutionary concept! A quick Google search revealed that,
funnily enough, I wasnâ€™t the first person to think of this (yes! Iâ€™d
been scooped!), but more importantly it led to what I think ought to be
three of the Standard Works of Open Science, Bill Hookerâ€™s three part
series on Open Science at 3 Quarks Daily
\[[1](http://3quarksdaily.blogs.com/3quarksdaily/2006/10/the_future_of_s_1.html),
[2](http://3quarksdaily.blogs.com/3quarksdaily/2006/11/the_future_of_s.html),
[3](http://3quarksdaily.blogs.com/3quarksdaily/2007/01/the_future_of_s.html)\],
Jean-Claude Bradleyâ€™s [presentation on Open Notebook Science at Nature
Precedings](http://precedings.nature.com/documents/39/version/1) (and
the associated [original blog post coining the
term](http://drexel-coas-elearning.blogspot.com/2006/09/open-notebook-science.html)),
and Deepak Singhâ€™s [talk on Open Science at Ignite
Seattle](http://mndoci.com/blog/2007/03/03/talking-open-science-at-ignite-seattle/).
From there I was inspired to seize the opportunity, get a blog of my
own, and get involved. The rest of my story story, so far, is more or
less available online
[here](http://blog.openwetware.org/scienceintheopen) and via the [usual
sources](http://www.google.co.uk/search?q=cameron+neylon).

Which leads me to ask. What got you involved in the â€˜openâ€™ movement?
What, for you, were the 'primary texts' of open science and open
research? There is a value in recording this, or at least our memories
of it, for ourselves, to learn from our mistakes and perhaps discern the
direction going forward. Perhaps it isnâ€™t even too self serving to
think of it as history in the making. Or perhaps, more in line with our
own aims as â€˜open scientistsâ€™, that we would be doing a poor job if
we didnâ€™t record what brought us to where we are and what is
influencing our thinking going forward. I think the blogosphere does a
pretty good job of the latter, but perhaps a little more recording of
the former would be helpful.


So Michael Nielsen, one morning at breakfast at Scifoo asked one of those questions which never has a short answer; â€˜So how did you get into this open science thing?â€™ and I realised that although I have told the story to many people I havenâ€™t ever written it down.

Publicaciones de Rogue Scholar

Open Data, Open Source, Open Process: Open Research

A personal view of Open Science – Part II – Tools

The Southampton Open Science Workshop – a brief report

Q&A in this week’s Nature – one or two (minor) clarifications

How I got into open science â€“ a tale of opportunism and serendipity