Interdisciplinary Innovation in International Initiatives

  • John C. Wooley
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3939)


Research in science and technology in the 21st century, emerging around the world in both academic and commercial settings, is characterized by the convergence of scientific disciplines and by the involvement of teams of investigators with diverse backgrounds. These developments reflect our increased knowledge about the complexity of nature, and correspondingly, the intellectual excitement that has grown at what were boundaries among disciplines. Over the past decade, deep, disciplinary expertise applied within multidisciplinary collaborations has been conducted on an ever larger scale, which has fostered many frontiers in interdisciplinary science. Scientific research at the interfaces – convergent science – presents significant challenges as well as opportunities: new organizational and technological approaches are necessary to enable the scale and scope of the human enterprise.

Examples of the research problems and the requisite intellectual skill sets and research environments have recently been articulated to summarize initial implementations of organizations exemplifying the opportunities of conver-gence and to provide a guide to action (Converging Sciences, 2005). We provide a further perspective on the context in which innovative efforts in converging sciences can successfully proceed; namely, the research will build upon a computing and information technology enabled research environment, that is, upon cyberinfrastructure. We explicate a specific early example of such a model, with novel organizational and technology features, that we hope can serve to inspire international efforts and enable comparable achievements.


Genomic Medicine International Initiative Protein Structure Initiative Disciplinary Expertise Biomedical Computing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • John C. Wooley
    • 1
  1. 1.Center for Research on Biosystems & Digitally enabled Genomic Medicine, California Institute on Telecommunications and Information TechnologyUniversity of CaliforniaSan Diego, La JollaUSA

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