If I were to crudely cobble together a book on the dissemination of scientific knowledge, then I would probably organise it into three parts. For the first, it would discuss how we evolved from tinkering apes; blindly and, at times, consciously experimenting with various technologies and methods. Over the next few millennia we would see a gradual shift from communal knowledge of tribal communities to the development of writing and its spawning of cultural institutions, such as libraries and universities. The second part of our book would place us in the year of 1665: here, we see the publication of the first journals, and with that the death of “cryptic anagrams, secret discoveries, and bitter turf wars”. During this period there is also a huge growth in the number of universities as well as an industrial scale dissemination of information thanks to Gutenberg’s printing press. Lastly, following the introduction of Peer Review, we arrive at the precursors for the third part of our book: the mass movement towards the digitisation of knowledge through computers and the internet.
So, in lieu of a formal introduction, here we are at Part Three of our story: welcome to Open Science.
In my lifetime I’ve seen travel agents made superfluous thanks to online comparison engines, encyclopaedias made freely available and editable, vast repositories of music, videos and computers games being just one click away, and the creation of intuitive methods of searching and sifting through the vast body of knowledge on the web. We are now facing a similar game-changing situation in science and academia. As a scientist in the 21st Century you are able to use a variety of Open Access resources to publish articles and books, share your data and code via online repositories, engage with the wider science community in a matter of seconds, and freely distribute your work through Creative Commons licences.
So, what is Open Science? Well, to save me the hassle, Wikipedia offers four general practices a budding researcher should strive for if they wish to become an open scientist:
- Publishing Open Research and Open Data;
- Campaigning for Open Access;
- Encouraging Open Notebook Science;
- Generally making it easier to publish, communicate and disseminate scientific knowledge.
Over the next couple of weeks I’ll touch on each of these topics. For now, I just want to generally describe how I currently see things in the landscape of academia and science. You might view our current situation as being a case of future shock: that is, there’s been a lot of change across science and academia in a relatively short space of time, with all of us struggling to keep apace. Open Access is a classic example: here, the rapid digitisation of books and journals, coupled with ease at which these items can be disseminated via the Internet, has resulted in a situation where the pre-defined roles of publishers, libraries and authors have in many respects started to blur. One challenge, then, is how does this ecology of players redefine themselves in a rapidly changing environment? At the moment, there aren’t any definitive answers, only suggestive trends of development. Many roads exist to unrestricted access of peer reviewed content and it is certainly the case that, in the short term, we are likely to see a rapid increase in the adoption of both publisher-based and self-archiving forms of Open Access.
In the publishing industry, for instance, the monograph has been in decline in recent times, yet with the rise of digitisation we see a potential opportunity for those savvy publishers to provide some financial backing (not available anywhere else on a mass scale) for its revival through Open Access. Not only is the publication of monographs efficient and cost-effective, it also offers a niche market for certain types of readers and authors (just see the Amazon Kindle Singles for an example of how they successfully marketed similar length works). Meanwhile, self-archiving offers an extension of the roles afforded to libraries and even individual researchers. We know the concept works: just look at the success of CiteSeer and arXiv.
For many of us, the current debate about Open Access, and Open Science more generally, is built on principles, rather than severe problems with access for those associated with academic institutions. If you’re an academic, especially in the West, then you’re already likely to have, for example, access to a particular journal article through library subscriptions. Failing that, there are normally preprints on an author’s page or, if you’re feeling slightly cheeky, you can always request an article through online communities (e.g. Reddit group Journal Share and the Pirate University). These factors alone probably explain some of the inertia in practicing Open Science in certain academic quarters. Yet, as we are currently witnessing, these calls for change are rapidly gathering momentum. Part of this is due to beliefs that have grown up with the Internet generation, as captured by the idea of information needs to be free. Such sentiments strike a chord with the scientific community and its spirit of collaboration. Indeed, the Panton Principles opens with the notion that science is based on building on, reusing and openly criticising the published body of scientific knowledge.
Still, we’re also taking steps in a new world, and with that comes an onslaught of new challenges and problems. Science is built on a network of communication and we are witnessing an ever increasing degree of complexity. A study by Bollen et al. (2009) beautifully demonstrated how a single discipline can intersect with several fields (see fig.1 below). Growing complexity, however, is not always a positive development from the perspective of the consumer. Take the ever increasing noise-to-signal ratio: “as you consume more data, the ratio of noise to signal increases, the less you know what’s going on and the more inadvertent trouble you are likely to cause”. Ironically, in a society that gleefully endorses ever growing supplies of information, one of our biggest challenges as consumers and producers is to ration this supply and become better equipped at finding signals in amongst the noise.
We’re only just scratching the surface here and I don’t have all the answers (far from it) on what the Open Science community wants. So, in the spirit of cooperation and guided evolution, I’m hoping that I can get feedback as to what people would like to see on the blog, as well as whether they’d be interested in offering contributions. At the moment, a lot of OA blogs straddle between activism and commentary, with little being said on actually how to do OA – that is, its policies, practices and standards. My goal for the Open Science blog is to try strike balance between all three of these aspects in an effort to provide a unique resource that the community can draw upon. So far, I’ve got a few contributors in the publishing industry, and hopefully in the next few weeks we’ll start seeing articles from them. I’m also interested in those individuals with insight into Open Data as well as anyone broadly committed to the principles of Open Science.
So, on that note, I look forward to seeing you all on the blog.
This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.
Bollen J, Van de Sompel H, Hagberg A, Bettencourt L, Chute R, Rodriguez MA, & Balakireva L (2009). Clickstream data yields high-resolution maps of science. PloS one, 4 (3) PMID: 19277205