Multi-Source Data Analysis Challenges

S. Uselton, L. Treinish, J. Ahrens, E. W. Bethel, A. State
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引用次数: 16

Abstract

Author(s): Uselton, S; Ahrens, J; Bethel, W; Treinish, L; State, A | Abstract: The factors making multi-source data analysis pervasive in the near future are: ease and cost effectiveness of digital data acquisition; fidelity, detail and practicality of computational simulations; and networks that make data from many sources accessible to a single user or application. Bringing data from multiple sources together is much more powerful than using each source separately, and computer systems can provide support for users in situations where they would be overwhelmed by volume or complexity without the support. However, multi-source data analysis still face challenges in the Accelerated Strategic Computing Initiative, geosciences, atmospheric sciences, medicine, and aerospace engineering design, and these challenges are presented.
多源数据分析挑战
作者:Uselton, s;Ahrens J;伯特利,W;Treinish L;摘要:在不久的将来,多源数据分析普及的因素是:数字数据采集的便捷性和成本效益;计算模拟的保真度、细节性和实用性;以及使单个用户或应用程序可以访问来自多个来源的数据的网络。将来自多个来源的数据结合在一起比单独使用每个来源的数据要强大得多,并且计算机系统可以在没有支持的情况下为用户提供支持,这些情况下用户可能会被数量或复杂性压垮。然而,多源数据分析在加速战略计算计划、地球科学、大气科学、医学和航空航天工程设计中仍然面临挑战,这些挑战被提出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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