Towards a Data-Centric Research and Development Roadmap for Large-scale Science User Facilities

被引:1
|
作者
Bethel, E. Wes [1 ]
机构
[1] Lawrence Berkeley Natl Lab, Berkeley, CA 94720 USA
来源
2017 IEEE 13TH INTERNATIONAL CONFERENCE ON E-SCIENCE (E-SCIENCE) | 2017年
关键词
D O I
10.1109/eScience.2017.72
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The U.S. Department of Energy (DOE) Office of Science (SC) operates approximately four dozen large-scale science user facilities (SUFs), each of which generates a tremendous amount of scientific data from experiments, observations and computations. To better understand the data needs and challenges, DOE has run many workshops in recent years to identify and articulate data-centric challenges and opportunities at varying resolution, from facility to community scale. Building on those workshop reports, as well as others from elsewhere in the community, this article goes beyond the findings-recommendations typical of workshop reports to consider how one might structure a broad, technology-and data-centric, coordinated research effort that would realize progress towards solutions that address the well documented challenges and opportunities. We focus on identifying practical issues of strategic relevance, along with offering a view about the focal points for a coordinated research and development effort that would target meeting data-centric needs of a broad set of science users and SUFs. These focal points would, by their nature, engage a spectrum of researchers from computer science, computational and experimental sciences, and data science in a coordinated fashion.
引用
收藏
页码:462 / 464
页数:3
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