University of Glasgow

Roderic Page

For fun I quickly programmed a little tool for bioGUID that makes use of
[Connotea\'s web api](http://www.connotea.org/wiki/WebAPI). When an
article is displayed, the page loads a Javascript script that makes a
call to a simple web service that looks up a reference in Connotea and
displays a tag cloud if the reference is found. For example, the paper
announcing Zoobank
([doi:10.1038/437477a](http://dx.doi.org/10.1038/437477a)) looks like
this:  
  
[![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgRzjGHVo4K4J1nZFzPJYtKThemHvlgAFp6cP5E9_7xmP17DhBxlhxPbrxSYPYOQtFhSdUKpF930kvF2rhnBGyCbzpVd-BjqxMQvhYO6nSV6koNsXVE-JNG44nY4SbXpOcLr9Qs/s400/Picture+2.png){#BLOGGER_PHOTO_ID_5326866308183852850
style="display:block; margin:0px auto 10px; text-align:center;cursor:pointer; cursor:hand;width: 400px; height: 323px;"
border="0"}](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgRzjGHVo4K4J1nZFzPJYtKThemHvlgAFp6cP5E9_7xmP17DhBxlhxPbrxSYPYOQtFhSdUKpF930kvF2rhnBGyCbzpVd-BjqxMQvhYO6nSV6koNsXVE-JNG44nY4SbXpOcLr9Qs/s1600-h/Picture+2.png){onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}"}  
The reference has been bookmarked by 6 people, using 15 tags, some more
popular than others. The tags and users are linked to Connotea.  
  
This service is can be accessed at
**http://bioguid.info/services/connotea.php?uri=**, for example
<http://bioguid.info/services/connotea.php?uri=doi:10.1038/437477a>. By
default it returns JSON (you can also set the name of the callback
function by add a **&callback=** parameter), but you can get HTML by
adding **&format=html**. The HTML is also included in the JSON result,
if you want to quickly display something, rather than roll your own.  
  
Basically the service takes the DOI you supply, converts it to an [MD5
hash](en.wikipedia.org/wiki/MD5), then looks it up in Connotea. There
were a few little \"gotcha\'s\", such as the fact that the Connotea user
may have bookmarked \"doi:10.1038/43747\" or the proxied version
\"http://dx.doi.org/10.1038/43747\", and these have different MD5
hashes. My service tries both variations and merges the results.


For fun I quickly programmed a little tool for bioGUID that makes use of Connotea's web api. When an article is displayed, the page loads a Javascript script that makes a call to a simple web service that looks up a reference in Connotea and displays a tag cloud if the reference is found.

Connotea tags

Cameron Neylon

*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.*


<em>
 The second installment of the paper (first part here) where I discuss building tools for Open (or indeed any) Science.
</em>
<strong>
 Tools for open science – building around the needs of scientists
</strong>
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 – Part II – Tools

So [Ian Mulvaney
asked](http://friendfeed.com/e/843063fc-1a40-e206-e18b-3178f1577d18/we-are-having-a-serious-think-about-Connotea-What/),
and as my solution [did not fit into the
margin](http://friendfeed.com/e/843063fc-1a40-e206-e18b-3178f1577d18/we-are-having-a-serious-think-about-Connotea-What/)
I thought I would post here. Following on from the
[two](http://cameronneylon.net/blog/facebooks-for-scientists-theyre-breeding-like-rabbits/)
[rants](http://cameronneylon.net/blog/an-open-letter-to-the-developers-of-social-network-and-%E2%80%98web-20%E2%80%99-tools-for-scientists/)
of a few weeks back and many discussions at Scifoo I have been thinking
about how scientists might be persuaded to make more use of social web
based tools. What does it take to get enough people involved so that the
network effects become apparent. I had a discussion with [Jamie
Heywood](http://en.wikipedia.org/wiki/James_Heywood) of [Patients Like
Me](http://www.patientslikeme.com/) at Scifoo because I was interested
as to why people with chronic diseases were willing to share detailed
and very personal information in a forum that is essentially public. His
response was that these people had an ongoing and extremely pressing
need to optimise *as far as is possible* their treatment regime and
lifestyle and that by correlating their experiences with others they got
to the required answers quicker. Essentially successful management of
their life required rapid access to high quality information sliced and
diced in a way that made sense to them and was presented in as efficient
and timely a manner as possible. Which obviously left me none the wiser
as to why scientists don't get it....

Nonetheless there are some clear themes that emerge from that
conversation and others looking at uptake and use of web based tools. So
here are my 5 thoughts. These are framed around the idea of reference
management but the principles I think are sufficiently general to apply
to most web services.

1.  Any tool must fit within my existing workflows. Once adopted I may
    be persuaded to modify or improve my workflow but to be adopted it
    has to fit to start with. For citation management this means that it
    must have one click filing (ideally from any place I might find an
    interesting paper)Â  but will also monitor other means of marking
    papers by e.g. shared items from Google reader, 'liked' items on
    Friendfeed, or scraping tags in del.icio.us.
2.  Any new tool must clearly outperform all the existing tools that it
    will replace in the relevant workflows *without the requirement for
    network or social effects*. Its got to be absolutely clear on first
    use that I am going to want to use this instead of e.g. Endnote.
    That means I absolutely have to be able to format and manage
    references in a word processor or publication document. Technically
    a nightmare I am sure (you've got to worry about integration with
    Word, Open Office, GoogleDocs, Tex) but an absolute necessity to get
    widespread uptake. And this has to be absolutely clear the first
    time I use the system, before I have created any local social
    network and before you have a large enough user base for theseto be
    effective.
3.  It must be near 100% reliable with near 100% uptime. Web services
    have a bad reputation for going down. People don't trust their
    network connection and are much happier with local applications
    still. Don't give them an excuse to go back to a local app because
    the service goes down. Addendum -- make sure people can easily
    backup and download their stuff in a form that will be useful even
    if your service dissappears. Obviously they'll never need to but it
    will make them feel better (and don't scrimp on this because they
    will check if it works).
4.  Provide at least one (but not too many) really exciting new feature
    that makes people's life better. This is related to \#2 but is
    taking it a step further. Beyond just doing what I already do better
    I need a quick fix of something new and exciting. My wishlist for
    Connotea is below.
5.  Prepopulate. Build in publically available information before the
    users arrive. For a publications database this is easy and this is
    something that [BioMedExperts](http://www.biomedexperts.com/) got
    right. You have a pre-existing social network and pre-existing
    library information. Populate 'ghost' accounts with a library that
    includes people's papers (doesn't matter if its not 100% accurate)
    and connections based on co-authorships. This will give people an
    idea of what the social aspect can bring and encourage them to bring
    more people on board.

So that is so much motherhood and applepie. And nothing that Ian didn't
already know (unlike some other developers who I shan't mention). But
what about those cool features? Again I would take a back to basics
approach. What do I actually want?

Well what I want is a service that will do three quite different things.
I want it to hold a library of relevant references in a way I can search
and use and I want to use this to format and reference documents when I
write them. I want it to help me manage the day to day process of
dealing with the flood of literature that is coming in (real time
search). And I want it to help me be more effective when I am
researching a new area or trying to get to grips with something (offline
search). Real time search I think is a big problem that isn't going to
be solved soon. The library and document writing aspects I think are a
given and need to be the first priority. The third problem is the one
that I think is amenable to some new thinking.

What I would really like to see here is a way of pivoting my view of the
literature around a specific item. This might be a paper, a dataset, or
a blog post. I want to be able to click once and see everything that
item cites, click again and see everything that cites it. Pivot away
from that to look at what GoPubmed thinks the paper is about and see
what it has which is related and then pivot back and see how many of
those two sets are common. What are the papers in this area that this
review isn't citing? Is there a set of *authors* this paper isn't
citing? Have they looked at all the datasets that they should have? Are
there general news media items in this area, books on Amazon, books in
my nearest library, books on *my* bookshelf? Are they any good? Have any
of my trusted friends published or bookmarked items in this area? Do
they use the same tags or different ones for this subject? What exactly
is Neil Saunders doing looking at that gene? Can I map all of my friends
tags onto a controlled vocabulary?

Essentially I am asking for is to be able to traverse the graph of how
all these things are interconnected. Most of these connections are
already explicit somewhere but nowhere are they all brought together in
a way that the user can slice and dice them the way they want. My belief
is that if you can start to understand how people use that graph
effectively to find what they want then you can start to automate the
process and that that will be the route towards real time search that
actually works.

...but you'll struggle with uptake...


So Ian Mulvaney asked, and as my solution did not fit into the margin I thought I would post here. Following on from the two rants of a few weeks back and many discussions at Scifoo I have been thinking about how scientists might be persuaded to make more use of social web based tools. What does it take to get enough people involved so that the network effects become apparent.

How to make Connotea a killer app for scientists

Leigh Dodds has a nice post [How Shall I Integrate Thee? Let Me Count
the Ways\...](http://www.ldodds.com/blog/archives/000314.html) about
different ways to integrate data.  

- The one where we share identifiers
- The one where we\'re describing the same thing
- The one where we\'re speaking different languages
- The one where we\'re using different units
- The one where we\'re speaking at different levels of abstraction

  
Apart from the suggestion that Leigh has been watching way too much
[Friends](http://en.wikipedia.org/wiki/List_of_Friends_episodes),
there\'s much food for thought here. I suspect that \"The one where
we\'re describing the same thing\" is the one I\'ll be making most use
of.  
  
In [Rethinking LSIDs versus HTTP
URI](http://iphylo.blogspot.com/2007/06/rethinking-lsids-versus-http-uri.html)
I argued that most applications will use HTTP URIs, which makes them
accessible, but not terribly useful as identifiers, the reason being
that I think it is unlikely that people will reuse HTTP URIs (\"The one
where we share identifiers\"). A good example is Connotea, which has its
own URIs for each paper its users bookmark. I won\'t use these URIs as
identifiers in my database (if only because if a user resolves them,
they get taken to Connotea\'s web site, not mine). However, I will store
any PubMed and DOI identifiers, so that somebody aggregating information
from Connotea (say to retrieve user tags) and my database (say, to get
links to sequences and specimens) can work out that the Connotea URI and
my URI are talking about the same thing.


Leigh Dodds has a nice post How Shall I Integrate Thee? Let Me Count the Ways... about different ways to integrate data.

Messaggi di Rogue Scholar

Connotea tags

A personal view of Open Science – Part II – Tools

How to make Connotea a killer app for scientists

How Shall I Integrate Thee? Let Me Count the Ways...