WORKSHOP: The Future of Scientific Knowledge Discovery in the Open Networked Environment

研讨会：开放网络环境中科学知识发现的未来

• 批准号: 1042078
• 负责人: Paul Uhlir
• 金额: $ 10万
• 依托单位: National Academy of Sciences
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1042078&HistoricalAwards=false
• 关键词: WORKSHOP; Future; Scientific; Knowledge; Discovery

The ways in which scientific knowledge is discovered and communicated openly online have changed dramatically over the last three decades, and especially in the last ten years. Multiple factors have contributed to massive growth in this area. The production of vast amounts of data and literature, coupled with the rapid development and advancement of the processing, storage, and communication technologies have made it both possible and necessary to use more computing technologies and methods in the research process. Computer-mediated discovery processes are being increasingly adopted and used by different scientific communities to explore and study a wide range of domains of knowledge, including all scientific disciplines. Computational scientific knowledge discovery is thus rapidly becoming practiced as a new form of scientific inquiry in the virtual environment, building upon and supplementing the research based on theoretical, experimental, and observational methods that preceded it. At the same time, many new models of open science have been developed that take much greater advantage of the capabilities of digital networks. When integrated together online, various types of open knowledge resources are forming incipient information ?commons? and knowledge environments, which can derive more value from the public investments in research. Of particular interest to this proposed project, such mechanisms can enable more efficient and effective applications of digital scientific knowledge discovery tools and techniques. A deeper understanding of the opportunities and barriers to such processes has the potential to accelerate the progress of scientific research, to support U.S. national competitiveness and increased productivity in information-intensive areas of research and its applications. An improved understanding of these issues also can enable research managers and policy makers to make much more informed decisions about the research enterprise, and to explain more clearly to policymakers and to the general public how the public investment in research and digital technologies advances broader socioeconomic interests.

在过去的三十年里，尤其是在过去的十年里，科学知识在网上公开发现和传播的方式发生了巨大的变化。多种因素促成了这一领域的大规模增长。大量数据和文献的产生，加上处理、存储和通信技术的快速发展和进步，使得在研究过程中使用更多的计算技术和方法成为可能和必要。不同的科学界越来越多地采用和使用以计算机为媒介的发现过程，以探索和研究广泛的知识领域，包括所有科学学科。因此，计算科学知识发现作为一种新的科学探究形式在虚拟环境中迅速得到实践，它建立在并补充了之前基于理论、实验和观察方法的研究基础上。与此同时，许多新的开放科学模型已经开发出来，这些模型更大程度地利用了数字网络的能力。当各种类型的开放知识资源在线整合在一起时，正在形成信息的雏形？公地？和知识环境，这可以从公共研究投资中获得更多价值。对这个拟议项目特别感兴趣的是，这种机制可以使数字科学知识发现工具和技术的应用更加高效和有效。 更深入地了解这些过程的机会和障碍，有可能加快科学研究的进展，支持美国的国家竞争力，提高信息密集型研究及其应用领域的生产力。对这些问题的更好理解也可以使研究管理者和政策制定者对研究企业做出更明智的决策，并更清楚地向政策制定者和公众解释研究和数字技术的公共投资如何促进更广泛的社会经济利益。