ABSTRACT
Alfons G. Hoekstra Section Computational Science, University of Amsterdam, Kruislaan 403, Amsterdam, The Netherlands, alfons@science.uva.nl
Simon Portegies Zwart Section Computational Science and Astronomical Institute “Anton Pannekoek,” University of Amsterdam, Kruislaan 403, Amsterdam, The Netherlands, spz@science.uva.nl
Marian Bubak Section Computational Science, University of Amsterdam, Kruislaan 403, Amsterdam, The Netherlands, and AGH University of Science and Technology, Krako´w, Poland, bubak@science.uva.nl
Peter M.A. Sloot Section Computational Science, University of Amsterdam, Kruislaan 403, Amsterdam, The Netherlands, sloot@science.uva.nl
Recent advances in experimental techniques have opened up new windows into physical and biological processes on many levels of detail. The resulting data explosion requires sophisticated techniques, such as grid computing and collaborative virtual laboratories, to register, transport, store, manipulate, and share the data. The complete cascade from the individual components to the fully integrated multi-science systems crosses many orders of magnitude
in temporal and spatial scales. The challenge is to study not only the fundamental processes on all these separate scales, but also their mutual coupling through the scales in the overall multi-scale system, and the resulting emergent properties. These complex systems display endless signatures of order, disorder, self-organization and self-annihilation. Understanding, quantifying and handling this complexity is one of the biggest scientific challenges of our time [8].
