{"id":464,"date":"2013-10-28T14:17:14","date_gmt":"2013-10-28T14:17:14","guid":{"rendered":"https:\/\/libraryblogs.is.ed.ac.uk\/datablog\/?p=464"},"modified":"2013-10-28T14:17:14","modified_gmt":"2013-10-28T14:17:14","slug":"science-as-an-open-enterprise-prof-geoffrey-boulton","status":"publish","type":"post","link":"https:\/\/libraryblogs.is.ed.ac.uk\/datablog\/2013\/10\/28\/science-as-an-open-enterprise-prof-geoffrey-boulton\/","title":{"rendered":"Science as an open enterprise \u2013 Prof. Geoffrey Boulton"},"content":{"rendered":"

\"\"<\/a>As part of Open Access Week<\/a>, the Data Library<\/a> and Scholarly Communications<\/a> teams in IS hosted a lecture by emeritus Professor Geoffrey Boulton<\/a>\u00a0drawing upon his study for the Royal Society: Science as an Open Enterprise (Boulton, et al 2012)<\/a>. The session was introduced by Robin Rice<\/a> who is the University of Edinburgh Data Librarian.\u00a0 Robin pointed out that the University of Edinburgh<\/a> was not just active, but was a leader in research data management having been the first UK institution to have a formal research data management policy.<\/a>\u00a0 Looking at who attended the event, perhaps unsurprisingly the majority were from the University of Edinburgh.\u00a0 Encouragingly, there was roughly a 50:50 split between those actively involved in research and those in support roles.\u00a0 I say encouragingly as it was later stated that often policies get high-level buy in from institutions but have little impact on those actually doing the research. Perhaps more on that later.<\/p>\n

For those that don\u2019t know Prof. Boulton, he is a geologist and glaciologist and has been actively involved in scientific research for over 40 years.\u00a0 He is used to working with big things (mountains, ice sheets) over timescales measured in millions of years rather than seconds and notes that\u00a0 while humanity is interesting it will probably be short lived!<\/p>\n

Arguably the way we have done science over the last three hundred years has been effective. Science furthers knowledge. \u00a0Boulton’s introduction made it clear that he wanted to talk about the processes of science and how they are affected by the gathering, manipulation and analysis of huge amounts of data: the implications, the changes in processes, and why evenness matters in the process of science. This was going to involve a bit of a history lesson, so let\u2019s go back to the start.<\/p>\n

Open is not a new concept<\/strong><\/p>\n

\"Geoffrey<\/a>

“Open is not a new concept”<\/em><\/p><\/div>\n

Open has been a buzzword for a few years now.\u00a0 Sir Tim Berners-Lee and Prof. Nigel Shadbolt <\/a>have made great progress in opening up core datasets to the public.\u00a0 But for science, is open a new concept? <\/span>Boulton thinks not. Instead he reckons that openness is at the foundations of science but has somehow got a bit lost recently.\u00a0 Journals originated as a vehicle to disseminate knowledge and trigger discussion of theories.\u00a0 Boulton \u00a0gave a brief history of the origins of journals pointing out that Henry Oldenburg<\/a> is credited with founding the peer review process with the Philosophical Transactions of the Royal Society<\/a>.\u00a0 The journal allowed scientists to share their thoughts and promote discussion.\u00a0 Oldenburg\u2019s insistence that the Transactions be published in the vernacular rather than Latin was significant as it made science more accessible.\u00a0 Sound familiar?<\/p>\n

Digital data – threat or opportunity?\u00a0<\/strong><\/p>\n

We are having the same discussions today, but they are based around technology and, perhaps in some cases, driven by money. The journal publishing model has changed considerably since Oldenburg and it was not the focus of the talk so let us concentrate on the data.\u00a0 Data are now largely digital.\u00a0 Journals themselves are also generally digital. \u00a0The sheer volume of data we now collect makes it difficult to include the data with a publication. So should data go into a repository?\u00a0 Yes, and some journals encourage this but few mandate it.\u00a0 Indeed, many of the funding councils state clearly that research output should be deposited in a repository but don\u2019t seem to enforce this.<\/p>\n

Replicability \u2013 the cornerstone of the scientific method<\/strong><\/p>\n

\"Image<\/a>

Geoffrey Boulton, mid-talk.<\/p><\/div>\n

Having other independent scientists replicate and validate your findings adds credence to them. Why would you as a professional scientist not want others to confirm that you are correct?\u00a0 It seems quite simple but it is not the norm.\u00a0 Boulton pointed us to a recent paper in Nature (Nature v483 n7391<\/a>) which attempted to replicate the results of a number of studies in cancer research. The team found that they could only replicate 6, around 11%, of the studies.\u00a0 So the other 81% were fabricating their results?\u00a0 No, there are a number of reasons why the team could not replicate all the studies.\u00a0 The methodology may not have been adequately explained leading to slightly different techniques being used, the base data may have been unobtainable and so on but the effect is the same. Most of the previous work that the team looked at is uncorroborated science.\u00a0 Are we to trust their findings?\u00a0 Science is supposed to be self-correcting.\u00a0 You find something, publish, others read it, replicate and corroborate or pose an alternative, old theories are discounted (Science 101 time: \u201cNull Hypothosis<\/a>“) and our collective knowledge is furthered.\u00a0 Boulton suggests that, to a large degree, this is not happening. Science is not being corroborated. We have forgotten the process on which our profession is based. Quoting Jim Gray:<\/p>\n

“when you go and look at what scientists are doing, day in and day out, in terms of data analysis, it is truly dreadful. We are embarrassed by our data.”<\/em><\/p><\/blockquote>\n

Moving forward (or backwards) towards open science<\/strong><\/p>\n

What do we need to do to support, to do to advise, to ensure materials are available for our students, for our researchers to ensure they can be confident about sharing their data? \u00a0The University of Edinburgh does reasonably well but we still, like most institutions, have things to do.<\/p>\n

Geoffrey looked at some of the benefits of open science and while I am sure we all already know what these are, it is useful to have some high profile examples that we can all aspire to following.<\/p>\n

    \n
  1. Rapid response \u2013 some scientific research is reactive. This is especially true in research into epidemiology and infectious diseases.\u00a0 An outbreak occurs, it is unfamiliar and we need to understand it as quickly as possible to limit its effects. During an e-coli outbreak in Hamburg local scientists were struggling to identify the source. They analysed the strain and released the genome under an open licence. Within a week they had a dozen reports from 4 continents. This helped to identify the source of the outbreak and ultimately saved lives.(Rohde et al 2011<\/a>)<\/em><\/li>\n
  2. Crowd-sourcing \u2013 mathematical research is unfathomable to many.\u00a0 Mathematicians are looking for solutions to problems. Working in isolation or small research clusters is the norm, but is it effective?\u00a0 Tim Gowers<\/a> (University of Cambridge) decided to break with convention and post the \u201cproblems\u201d he was working on to his blog<\/a>.\u00a0 The result; 32 days \u2013 27 people \u2013 800 substantive contributions. 800 substantive contributions!\u00a0 I am sure that Tim also fostered some new research collaborations from his 27 respondents.<\/li>\n
  3. Change the social dynamic of science – “We are scientists, you wouldn’t understand” is not exactly a helpful stance to adopt. \u00a0“We are scientists and we need your help,” now that\u2019s much better! \u00a0The rise of the app has seen a new arm of science emerge, “citizen science”. The crowd, or sometimes the informed crowd, is a powerful thing. With a carefully designed app you can collect a lot of data from a lot of places over a short period. Projects such as ASHtag<\/a> and LeafWatch<\/a> are just two examples where the crowd has been usefully deployed to help collect data for scientists.\u00a0 Actually, this has been going on for some time in different forms, do you remember the SETI@Home<\/a> screensaver?\u00a0 It\u2019s still going, 3 million users worldwide processing data for scientists since 1999.<\/li>\n
  4. Openness and transparency \u2013 no one wants another “Climategate<\/a>“.\u00a0 In fact Climategate need not have happened at all. Much of the data was already publicly available and the scientists had done nothing wrong. Their lack of openness was seen as an admission that they had something to hide and this was used to damaging effect by the climate sceptics.<\/li>\n
  5. Fraud \u2013 open data is crucial as it shines the light on science and the scientific technique and helps prevent fraud.<\/li>\n<\/ol>\n

    What value if not intelligent?<\/strong><\/p>\n

    However, Boulton’s closing comments made the point that openness has little value if it is not “intelligent” so this means it is:<\/p>\n