Accelerating Science: A Computing Research Agenda
Accelerating Science: A Computing Research Agenda
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发表时间：
2016-04
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通讯作者：
Vasant G Honavar;M. Hill;K. Yelick
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作者：
Vasant G Honavar;M. Hill;K. Yelick
作者：Honavar，Vasant G; Hill，Mark D; Yelick，凯瑟琳|摘要：“大数据”的出现不仅为加速科学进步，而且为实现新的发现模式提供了前所未有的机会。许多学科的科学进步越来越多地得益于我们通过计算透镜检查自然现象的能力，即，使用算法或信息处理抽象的基础过程;和我们的能力，以获取，共享，集成和分析不同类型的数据。然而，在我们获取、存储和处理数据的能力与我们有效利用数据推进发现的能力之间存在巨大差距。尽管数据管理和分析的常规方面已经成功实现了自动化，但科学过程的大多数要素目前都需要大量的人力专业知识和努力。加速科学以跟上数据采集和数据处理的速度，需要开发算法或信息处理抽象，再加上用于建模和模拟自然过程的正式方法和工具，以及科学家认知工具的重大创新，即，利用和扩展人类智力范围的计算工具，并在科学发现的广泛任务中与人类合作（例如，以闭环方式识别、优先化制定问题，设计、优先化和执行设计用于回答所选问题的实验，得出推论和评估结果，以及制定新问题）。这就要求协调一致的研究议程，旨在：发展，分析，整合，共享和模拟的算法或信息处理抽象的自然过程，再加上正式的方法和工具，他们的分析和模拟;创新的认知工具，增强和扩展人类的智力和伙伴与人类在科学的各个方面。
Author(s): Honavar, Vasant G; Hill, Mark D; Yelick, Katherine | Abstract: The emergence of "big data" offers unprecedented opportunities for not only accelerating scientific advances but also enabling new modes of discovery. Scientific progress in many disciplines is increasingly enabled by our ability to examine natural phenomena through the computational lens, i.e., using algorithmic or information processing abstractions of the underlying processes; and our ability to acquire, share, integrate and analyze disparate types of data. However, there is a huge gap between our ability to acquire, store, and process data and our ability to make effective use of the data to advance discovery. Despite successful automation of routine aspects of data management and analytics, most elements of the scientific process currently require considerable human expertise and effort. Accelerating science to keep pace with the rate of data acquisition and data processing calls for the development of algorithmic or information processing abstractions, coupled with formal methods and tools for modeling and simulation of natural processes as well as major innovations in cognitive tools for scientists, i.e., computational tools that leverage and extend the reach of human intellect, and partner with humans on a broad range of tasks in scientific discovery (e.g., identifying, prioritizing formulating questions, designing, prioritizing and executing experiments designed to answer a chosen question, drawing inferences and evaluating the results, and formulating new questions, in a closed-loop fashion). This calls for concerted research agenda aimed at: Development, analysis, integration, sharing, and simulation of algorithmic or information processing abstractions of natural processes, coupled with formal methods and tools for their analyses and simulation; Innovations in cognitive tools that augment and extend human intellect and partner with humans in all aspects of science.