Science at the speed of thought

Authors:
Judith E. Devaney;S. G. Satterfield;J. G. Hagedorn;J. T. Kelso;A. P. Peskin;W. L. George;T. J. Griffin;H. K. Hung;R. D. Kriz
Affiliations:
National Institute of Standards and Technology;National Institute of Standards and Technology;National Institute of Standards and Technology;National Institute of Standards and Technology;National Institute of Standards and Technology;National Institute of Standards and Technology;National Institute of Standards and Technology;National Institute of Standards and Technology;Virginia Tech
Venue:
Ambient Intelligence for Scientific Discovery
Year:
2005

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Abstract

Scientific discoveries occur with iterations of theory, experiment, and analysis. But the methods that scientists use to go about their work are changing [1]. Experiment types are changing. Increasingly, experiment means computational experiment [2], as computers increase in speed, memory, and parallel processing capability. Laboratory experiments are becoming parallel as combinatorial experiments become more common. Acquired datasets are changing. Both computer and laboratory experiments can produce large quantities of data where the time to analyze data can exceed the time to generate it. Data from experiments can come in surges where the analysis of each set determines the direction of the next experiments. The data generated by experiments may also be non-intuitive. For example, nanoscience is the study of materials whose properties may change greatly as their size is reduced [3]. Thus analyses may benefit from new ways to examine and interact with data.