Can Network Measures Serve as Indicators of Knowledge Creation and Flow? A Workshop Proposal

政府资助的研究与开发（R D）被广泛认为是提供社会和经济价值，其全部程度是具有挑战性的衡量。研究与发展活动的范围-假设、试验、反思-涉及在评价过程中很少看到或考虑到的交流过程。然而，我们知道，有效和高效的沟通对于取得最佳成果至关重要。衡量或深入了解这些过程的挑战意味着资助者对如何指导或评估科学传播知之甚少。很少有研究试图量化或评估研发中这些“无形”过程的贡献。本次研讨会将汇集领先的理论家，分析师和用户，探讨网络措施是知识创造的动态指标的可能性。网络分析提供了工具和措施来分析科学研究中的通信互动。随着先进计算技术的出现，网络分析作为研究通信过程的一种工具，已经变得非常活跃。可以建立巨大的网络，如万维网或科学家之间的全球联系。演绎推理已被应用到这些网络中，因为已经观察到了共同的模式。令人惊讶的是，许多现实世界的网络都表现出高度可重复性和普遍性的特征。这些功能表明，网络分析可以作为他们所代表的基本活动的指标，帮助评估，规划和指导与中心，集群和流动新兴的科学研究动态的可能指标。虽然我们仍然缺乏一个通用的预测框架，可以使用统一的理论工具来处理动态模型，但有可能开始标准化基础科学中与通信过程相关的措施。

Government sponsored research and development (R&D) is widely viewed as providing social and economic value whose full extent is challenging to measure. The spectrum of R&D activities - hypotheses, trials, reflections - involves communications processes that are rarely seen or accounted for in evaluation processes. Yet we know that effective and efficient communications are essential for optimal outcomes. The challenge of measuring or gaining insight into these processes means that funders understand little about how to guide or assess communications within science. Very few studies have attempted to quantify or assess the contribution of these "intangible" processes within R&D. This workshop will bring together leading theorists, analysts, and users to explore the possibility that network measures are indicators of dynamics of knowledge creation.Network analysis offers tools and measures to analyze communications interactions in scientific research. With the advent of advanced computing, network analysis has been vitalized as a tool for studying communications processes. Huge networks, such as the Worldwide Web or global linkages among scientists, can be created. Deductive reasoning has been applied to these networks as common patterns have been observed. Amazingly, many real-world networks have been shown to exhibit highly reproducible and often universal characteristics. These features suggest that network analysis may serve as indicators of the underlying activities which they represent, aiding evaluation, planning, and guidance with centrality, clustering, and flows emerging as possible indicators of dynamics in science research. While we continue to lack a general predictive framework that can treat dynamical models using unified theoretical tools, it may be possible to begin to standardize measures related to communications processes within basic sciences.