Data Farming around the world overview
Data Farming around the world overview
复制标题
世界各地的数据农业概述
DOI：
10.1109/wsc.2008.4736222
复制
发表时间：
2008
期刊：
影响因子：
--
通讯作者：
Klaus
中科院分区：
文献类型：
--
作者：
G. Horne;Klaus
数据农场将某些仿真模型固有的快速原型能力与高性能计算的探索能力相结合，以快速生成对问题的洞察力。数据养殖过程关注的是系统可能反应的更完整的图景，而不是试图找出一个答案。数据农业使决策者能够更全面地了解各种可能性，并考虑可能发现的异常值。在过去十年中，围绕这些理念形成了一个国际社会。2008年，第16届国际数据农业研讨会在美国加利福尼亚州蒙特雷举行，第17届研讨会在德国加米施帕滕基兴举行。除了对这两个研讨会进行总结之外，本文还将概述已经发展到包括国际数据农业社区的方法和应用的发展的过程。
Data farming combines the rapid prototyping capability inherent in certain simulation models with the exploratory power of high performance computing to rapidly generate insight into questions. The data farming process focuses on a more complete landscape of possible system responses, rather than attempting to pinpoint an answer. Data farming allows decision makers to more fully understand the landscape of possibilities and also consider outliers that may be discovered. Over the past decade, an international community has formed around these ideas. In 2008, International Data Farming Workshop 16 took place in Monterey, California, USA and workshop number 17 was held in Garmisch Partenkirchen, Germany. In addition to a summary of these two workshops, this paper will present an overview of the process that has developed to include the development of both methods and applications in the international data farming community.