Jim Gray's fourth paradigm and the construction of the scientific record
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چکیده
i n the latter part of his career, Jim Gray led the thinking of a group of scholars who saw the emergence of what they characterized as a fourth paradigm of scientific research. In this essay, I will focus narrowly on the implications of this fourth paradigm, which I will refer to as " data-intensive science " [1], for the nature of scientific communication and the scientific record. Gray's paradigm joins the classic pair of opposed but mutually supporting scientific paradigms: theory and experimentation. The third paradigm—that of large-scale computational simulation— emerged through the work of John von Neumann and others in the mid-20th century. In a certain sense, Gray's fourth paradigm provides an integrating framework that allows the first three to interact and reinforce each other, much like the traditional scientific cycle in which theory offered predictions that could be experimentally tested, and these experiments identified phenomena that required theoretical explanation. The contributions of simulation to scientific progress, while enormous, fell short of their initial promise (for example, in long-term weather prediction) in part because of the extreme sensitivity of complex systems to initial conditions and chaotic behaviors [2]; this is one example in which simulation, theory, and experiment in the context of massive amounts of data must all work together. To understand the effects of data-intensive science on the
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تاریخ انتشار 2009