Tuesday, 1 November 2011

to collaborate or not to collaborate

A few quotes from a fascinating new book, Collaborative Computational Technologies for Biomedical Research (Wiley, 2011):

Even within an institution — which should be legally, strategically, and financially incented for alignment, and for maximizing the opportunities for internal collaboration — barriers still exist. The subunits of the institution: its departments, its divisions, its components produce collaboration “walls” of varying substantiality. Organizational lore and personal relationships add another layer of “not-invented here” (NIH) culture, and allegiances to local agendas, even to the point of disadvantaging the larger institutional unit. In fact, if we wish to pursue the elimination of collaboration barriers we have to realize that many barriers are not institutional at all. Choices to collaborate or not collaborate are sometimes based not just on current affiliations but on past affiliations, degrees obtained, reputations, and even a less than rational bias as to just who our collaboration partners should be.
Alpheus Bingham (Foreword)

Many people who enter the field of scientific research are inherently introspective or shy; others possess minds that are highly logical and analytic. Many scientists were loners at school, perhaps never participating in team activities, such as sports or group governance. <...> People without great collaborative skills may engage in criticism, blame, negativity, and back-biting, often when under high stress. They may horde information for fear it will be used improperly. They may withdraw when others need them most or engage in manipulative behavior to get the attention or credit they yearn for. They many not communicate well, especially listening carefully, and may not understand the human side of technical information.

...Large-scale voluntary collaboration systems show remarkably consistent patterns in contributors’ behavior within scientific collaborations in the pharmaceutical industry and extending to every other company and industry examined. This behavior has all the signatures of a power law, driven by positive feedback from the individual and the group, and with a “long tail” such that approximately half of all contributions come from people who contribute only once to any given campaign. Interestingly the evidence also suggests that networks of acquaintanceship are not an essential driving force, which makes us revise our concept of “community”.
Robin W. Spencer (Chapter 6)

So, not surprisingly, what has happened in the past 20 years or so is biologists and chemical biologists (chemists working in biology) have resorted to data collecting. Genomics, proteomics, metabolomics, structural biology [X-ray and nuclear magnetic resonance (NMR)], chemical libraries, high-throughput assays, and so on, have been essentially data-collecting exercises. The “exciting discoveries” are made by robots, machines, and computers which collect enormous amounts of data. In the process human thought often seems to have become of secondary importance. At the same time, creative collaborations between chemists and biologists are often marginalized and starved for the resources...
Victor J. Hruby (Chapter 7)

Charles Darwin is an example of someone who acquired vast amounts of biological data from his correspondence with fellow naturalists and others with intimate knowledge of the natural world. Although the Victorian postal service that he used was comparatively efficient compared with today’s “snail mail” (and Darwin’s correspondence was prodigious), the need to communicate by letter writing inevitably slowed the development of his ideas on evolution. A modern Darwin alive today would be able to condense decades of networking into a few years, but it is interesting to speculate whether this speed would come at the expense of deep critical thought undertaken at a more leisurely pace.
Edward D. Zanders (Chapter 10)

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