Very final countdown to Science Online 09

I should be putting something together for the actual sessions I am notionally involved in helping running but this being a very interactive meeting perhaps it is better to leave things to very last minute. Currently I am at a hotel at LAX awaiting an early flight tomorrow morning. Daily temperatures in the LA area have been running around 25-30 C for the past few days but we’ve been threatened with the potential for well below zero in Chapel Hill. Nonetheless the programme and the people will more than make up for it I have no doubt. I got to participate in a bit of the meeting last year via streaming video and that was pretty good but a little limited – not least because I couldn’t really afford to stay up all night unlike some people who were far more dedicated.

This year I am involved in three sessions (one on Blog Networks, one on Open Notebook Science, and one on Social Networks for Scientists – yes those three are back to back…) and we will be aiming to be video casting, live blogging, posting slides, images, and comments; the whole deal. If you’ve got opinions then leave them at the various wiki pages (via the programme) or bring them along to the sessions. We are definitely looking for lively discussion. Two of these are being organised with the inimitable Deepak Singh who I am very much looking forward to finally meeting in person – along with many others I feel I know quite well but have never met – and others I have met and look forward to catching up with including Jean-Claude who has instigated the Open Notebook session.

With luck I will get to the dinner tomorrow night so hope to see some people there. Otherwise I hope to see many in person or online over the weekend. Thanks for Bora and Anton and David for superb organisation (and not a little pestering to make sure I decided to come!)

Convergent evolution of scientist behaviour on Web 2.0 sites?

A thought sparked off by a comment from Maxine Clarke at Nature Networks where she posted a link to a post by David Crotty. The thing that got me thinking was Maxine’ statement:

I would add that in my opinion Cameron’s points about FriendFeed apply also to Nature Network. I’ve seen lots of examples of highly specific questions being answered on NN in the way Cameron describes for FF…But NN and FF aren’t the same: they both have the same nice feature of discussion of a partiular question or “article at a URL somewhere”, but they differ in other ways,…[CN- my emphasis]

Alright, in isolation this doesn’t look like much, read through both David’s post and the comments, and then come back to Maxine’s,  but what struck me was that on many of these sites many different communities seem to be using very different functionality to do very similar things. In Maxine’s words ‘…discussion of a…paricular URL somewhere…’ And that leads me to wonder the extent to which all of these sites are failing to do what it is that we actually want them to do. And the obvious follow on question: What is it we want them to do?

There seem to be two parts to this. One, as I wrote in my response to David, is that a lot of this is about the coffee room conversation, a process of building and maintaining a social network. It happens that this network is online, which makes it tough to drop into each others office, but these conversational tools are the next best thing. In fact they can be better because they let you choose when someone can drop into your office, a choice you often don’t have in the physical world. Many services; Friendfeed, Twitter, Nature Networks, Faceboo, or a combination can do this quite well – indeed the conversation spreads across many services helping the social network (which bear in mind probably actually has less than 500 total members) to grow, form, and strengthen the connections between people.

Great. So the social bit, the bit we have in common with the general populace, is sorted. What about the science?

I think what we want as scientists is two things. Firstly we want the right URL delivered at the right time to our inbox (I am assuming anything important is a resource on the web – this may not be true now but give it 18 months and it will be) . Secondly we want a rapid and accurate assessment of this item, its validity, its relevance, and its importance to us judged by people we trust and respect. Traditionally this was managed by going to the library and reading the journals – and then going to the appropriate conference and talking to peopl. We know that the volume of material and the speed at which we need to deal with this is way too fast. Nothing new there.

My current thinking is that we are failing in building the right tools because we keep thinking of these two steps as separate when actually combining them into one integrated process would actual provide efficiency gains for both phases. I need to sleep on this to get it straight in my head, there are issues of resource discovery, timeframes, and social network maintenance that are not falling into place for me at the moment, so that will be the subject of another post.

However, whether I am right or wrong in that particular line of thought, if it is true that we are reasonably consistent in what we want then it is not suprising that we try to bend the full range of services available into achieving those goals. The interesting question is whether we can discern what the killer app would be by looking at the details of what people do to different services and where they are failing. In a sense, if there is a single killer app for science then it should be discernable what it would do based on what scientists try to do with different services…

Can post publication peer review work? The PLoS ONE report card

This post is an opinion piece and not a rigorous objective analysis. It is fair to say that I am on the record as and advocate of the principles behind PLoS ONE and am also in favour of post publication peer review and this should be read in that light. [ed I’ve also modified this slightly from the original version because I got myself mixed up in an Excel spreadsheet]

To me, anonymous peer review is, and always has been, broken. The central principle of the scientific method is that claims and data to support those claims are placed, publically, in the view of expert peers. They are examined, and re-examined on the basis of new data, considered and modified as necessary, and ultimately discarded in favour of an improved, or more sophisticated model. The strength of this process is that it is open, allowing for extended discussion on the validity of claims, theories, models, and data. It is a bearpit, but one in which actions are expected to take place in public (or at least community) view. To have as the first hurdle to placing new science in the view of the community a process which is confidential, anonymous, arbitrary, and closed, is an anachronism.

It is, to be fair, an anachronism that was necessary to cope with rising volumes of scientific material in the years after the second world war as the community increased radically in size. A limited number of referees was required to make the system manageable and anonymity was seen as necessary to protect the integrity of this limited number of referees. This was a good solution given the technology of the day. Today, it is neither a good system, nor an efficient system, and we have in principle the ability to do peer review differently, more effectively, and more efficiently. However, thus far most of the evidence suggests that the scientific community dosen’t want to change. There is, reasonably enough, a general attitude that if it isn’t broken it doesn’t need fixing. Nonetheless there is a constant stream of suggestions, complaints, and experimental projects looking at alternatives.

The last 12-24 months have seen some radical experiments in peer review. Nature Publishing Group trialled an open peer review process. PLoS ONE proposed a qualitatively different form of peer reivew, rejecting the idea of ‘importance’ as a criterion for publication. Frontiers have developed a tiered approach where a paper is submitted into the ‘system’ and will gradually rise to its level of importance based on multiple rounds of community review. Nature Precedings has expanded the role and discipline boundaries of pre-print archives and a white paper has been presented to EMBO Council suggesting that the majority of EMBO journals be scrapped in favour of retaining one flagship journal for which papers would be handpicked from a generic repository where authors would submit, along with referees’ reports and author’s response, on payment of a submission charge. Of all of these experiments, none could be said to be a runaway success so far with the possible exception of PLoS ONE. PLoS ONE, as I have written before, succeeded precisely because it managed to reposition the definition of ‘peer review’. The community have accepted this definition, primarily because it is indexed in PubMed. It will be interesting to see how this develops.

PLoS has also been aiming to develop ratings and comment systems for their papers as a way of moving towards some element of post publication peer review. I, along with some others (see full disclosure below) have been granted access to the full set of comments and some analytical data on these comments and ratings. This should be seen in the context of Euan Adie’s discussion of commenting frequency and practice in BioMedCentral journals which broadly speaking showed that around 2% of papers had comments and that these comments were mostly substantive and dealt with the science. How does PLoS ONE compare and what does this tell us about the merits or demerits of post publication peer review?

PLoS ONE has a range of commenting features, including a simple rating system (on a scale of 1-5) the ability to leave freetext notes, comments, and questions, and in keeping with a general Web 2.o feel the ability to add trackbacks, a mechanism for linking up citations from blogs. Broadly speaking a little more than 13% (380 of 2773) of all papers have ratings and around 23% have comments, notes, or replies to either (647 of 2773, not including any from PLoS ONE staff) . Probably unsurprisingly most papers that have ratings also have comments. There is a very weak positive correlation between the number of citations a paper has received (as determined from Google Scholar) and the number of comments (R^2 = 0.02, which is probably dominated by papers with both no citations and no comments, which are mostly recent, none of this is controlled for publication date).

Overall this is consistent with what we’d expect. The majority of papers don’t have either comments or ratings but a significant minority do. What is slightly suprising is that where there is arguably a higher barrier to adding something (click a button to rate versus write a text comment) there is actually more activity. This suggests to me that people are actively uncomfortable with rating papers versus leaving substantive comments. These numbers compare very favourably to those reported by Euan on comments in BioMedCentral but they are not yet moving into the realms of the majority. It should also be noted that there has been a consistent  programme at PLoS ONE with the aim of increasing the involvement of the community. Broadly speaking I would say that the data we have suggest that that programme has been a success in raising involvement.

So are these numbers ‘good’? In reality I don’t know. They seem to be an improvement on the BMC numbers arguing that as systems improve and evolve there is more involvement. However, one graph I received seems to indicate that there isn’t an increase in the frequency of comments within PLoS ONE over the past year or so which one would hope to see. Has this been a radical revision of how peer review works? Well not yet certainly, not until the vast majority of papers have ratings, but more importantly not until we have evidence that people are using those ratings. We are not yet in a position where we are about to see a stampede towards radically changed methods of peer review and this is not surprising. Tradition changes slowly – we are still only just becoming used to the idea of the ‘paper’ being something that goes beyond a pdf, embedding that within a wider culture of online rating and the use of those ratings will take some years yet.

So I have spent a number of posts recently discussing the details of how to make web services better for scientists. Have I got anything useful to offer to PLoS ONE? Well I think some of the criteria I suggested last week might be usefully considered. The problem with rating is that it lies outside the existing workflow for most people. I would guess that many users don’t even see the rating panel on the way into the paper. Why would people log into the system to look at a paper? What about making the rating implicit when people bookmark a paper in external services? Why not actually use that as the rating mechanism?

I emphasised the need for a service to be useful to the user before there are any ‘social effects’ present. What can be offered to make the process of rating a paper useful to the single user in isolation? I can’t really see why anyone would find this useful unless they are dealing with huge number of papers and can’t remember which one is which from day to day. It may be useful within groups or journal clubs but all of these require a group to sign up.  It seems to me that if we can’t frame it as a useful activity for a single person then it will be difficult to get the numbers required to make this work effectively on a community scale.

In that context, I think getting the numbers to around the 10-20% level for either comments or ratings has to be seen as an immense success. I think it shows how difficult it is to get scientists to change their workflows and adopt new services. I also think there will be a lot to learn about how to improve these tools and get more community involvement. I believe strongly that we need to develop better mechanisms for handling peer review and that it will be a very difficult process getting there. But the results will be seen in more efficient dissemination of information and more effective communication of the details of the scientific process. For this PLoS, the PLoS ONE team, as well as other publishers, including BioMedCentral, Nature Publishing Group, and others, that are working on developing new means of communication and improving the ones we have deserve applause. They may not hit on the right answer first off, but the current process of exploring the options is an important one, and not without its risks for any organisation.

Full disclosure: I was approached along with a number of other bloggers to look at the data provided by PLoS ONE and to coordinate the release of blog posts discussing that data. At the time of writing I am not aware of who the other bloggers are, nor have I read what they have written. The data that was provided included a list of all PLoS ONE papers up until 30 July 2008, the number of citations, citeulike bookmarks, trackbacks, comments, and ratings for each paper. I also received a table of all comments and a timeline with number of comments per month. I have been asked not to release the raw data and will honour that request as it is not my data to release. If you would like to see the underlying data please get in contact with Bora Zivkovic.

How to make Connotea a killer app for scientists

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. I had a discussion with Jamie Heywood of Patients Like Me 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)  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 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…

An open letter to the developers of Social Network and ‘Web 2.0’ tools for scientists

My aim is to email this to all the email addresses that I can find on the relevant sites over the next week or so, but feel free to diffuse more widely if you feel it is appropriate.

Dear Developer(s)

I am writing to ask your support in undertaking a critical analysis of the growing number of tools being developed that broadly fall into the category of social networking or collaborative tools for scientists. There has been a rapid proliferation of such tools and significant investment in time and effort for their development. My concern, which I wrote about in a recent blog post (here), is that the proliferation of these tools may lead to a situation where, because of a splitting up of the potential user community, none of these tools succeed.

One route forward is to simply wait for the inevitable consolidation phase where some projects move forward and others fail. I feel that this would be missing an opportunity to critically analyse the strengths and weaknesses of these various tools, and to identify the desirable characteristics of a next generation product. To this end I propose to write a critical analysis of the various tools, looking at architecture, stability, usability, long term funding, and features. I have proposed some criteria and received some comments and criticisms of these. I would appreciate your views on what the appropriate criteria are and would welcome your involvement in the process of writing this analysis. This is not meant as an attack on any given service or tool, but as a way of getting the best out of the development work that has already taken place, and taking the opportunity to reflect on what has worked and what has not in a collaborative and supportive fashion.

I will also be up front and say that I have an agenda on this. I would like to see a portable and agreed data model that would enable people to utilise the best features of all these services without having to rebuild their network within each site. This approach is very much part of the data portability agenda and would probably have profound implications for the design architecture of your site. My feeling, however, is that this would be the most productive architectural approach. It does not mean that I am right of course and I am prepared to be convinced otherwise if the arguments are strong.

I hope you will feel free to take part in this exercise and contribute. I do believe that if we take a collaborative approach then it will be possible to identify the features and range of services that the community needs and wants. Please comment at the blog post or request access to the GoogleDoc where we propose to write up this analysis.

Yours sincerely,

Cameron Neylon

Facebooks for scientists – they’re breeding like rabbits!

I promised some of you I would do this a while ago and I simply haven’t got to it. But enough of the excuses. There has been a huge number of launches in the past few months of sites and services that are intended to act as social network sites for scientists. These join a number of older services including Nature Network, OpenWetWare, and others. My concern is that with so many sites in the same space there is a risk none of them will succeed because the user community will be too diluted. I am currently averaging around three emails a week, all from different sites, suggesting I should persuade more people to sign up.

What I would like to do is attempt a critical and comprehensive analysis of the sites and services available as part of an exercise in thinking about how we might rationally consolidate this area, and how we might enable the work that has gone into building these services be used effectively to build the ‘next generation’ of sites. All of these sites have good features and it would be a shame to see them lost. I also don’t want to see people discouraged from building new and useful tools. I just want to see this work.

My dream would be to see an open source framework with an open data model that allows people to move their data from one place to another depending on what features they want. Then the personal networks can spread through the communities of all of these sites rather than being restricted to one, and the community can help build features that they want. As someone else said ‘Damnit, we’re scientists, we hold the stuff of the universe in our hands’ – can’t we have a think about what the best way to do this is?

What I want to do with this post is try to put together a comprehensive list of sites and services, including ones that get heavy scientific use but are not necessarily designed for scientists. I will miss many so please comment to point this out and I will add them. Then I want to try and put together a list of criteria as to how we might compare and contrast. Again please leave comments feel free to argue. I don’t expect this to necessarily be an easy or straightforward process, and I don’t expect to get complete agreement. But I am worried if things are just left to run that none of these sites will get the amount of support that is needed to make them viable.

So here goes.

Sites

Blog collections: Nature Network, ScienceBlogs, Scientific Blogging, WordPress, Blogspot, (OpenWetWare),

Social Networks: Laboratree, Ologeez, Research Gate, Epernicus, LabMeeting, Graduate Junction, (Nature Network), oh and Facebook, and Linkedin

Protocol sharing: Scivee, Bioscreencast, OpenWetWare, YouTube, lots of older ones I can’t remember at the moment

Others: Friendfeed, Twitter, GoogleDocs, GoogleGroups, Upcoming, Seesmic,

Critical criteria

Stability: funding, infrastructure, uptime, scalability, slashdot resistance, long term personnel committment

Architecture: open data model? ability to export data? compatibility with other sites? plugins? rss?

Design: user interface, ‘look’,  responsiveness

Features: what features do you think are important? I don’t even want to start putting my own predjudices here.

How to take this forward?

Comment here or at Friendfeed, or anywhere else, but if you can please tag the page with Fb4Sci. I have put up a GoogleDoc which is visible at http://docs.google.com/Doc?id=dhs5x5kr_572hccgvcct (current just contains this post). If you want access drop me an email at cam eron ney lon (no spaces) at googlemail (not gmail) and I will give anyone who requests editing rights. Comment and contributions from the development teams is welcome but I expect everyone to make a conflict of interest declaration. Mine is:

I blog at OpenWetWare and use the wiki extensively. I have been known to ring into steering committee meetings and have discussed specific features with the development team. I am an irregular user of Nature Network and a regular user of Friendfeed and Twitter. I have a strong bias towards open data models and architectures.

[ducks]