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…

Friendfeed, lifestreaming, and workstreaming

As I mentioned a couple of weeks or so ago I’ve been playing around with Friendfeed. This is a ‘lifestreaming’ web service which allows you to aggregate ‘all’ of the content you are generating on the web into one place (see here for mine). This is interesting from my perspective because it maps well onto our ideas about generating multiple data streams from a research lab. This raw data then needs to be pulled together and turned into some sort of narrative description of what happened. Continue reading “Friendfeed, lifestreaming, and workstreaming”