TLS- Measuring and Tracking Research Knowledge Integration

TLS-测量和跟踪研究知识整合

• 批准号: 0830207
• 负责人: Alan Porter
• 金额: $ 39.27万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-15 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0830207&HistoricalAwards=false
• 关键词: TLS; Measuring; Tracking; Research; Knowledge

Enhanced Science of Science and Innovation Policy depends on better metrics. You can't manage what you can't measure. This is particularly true for interdisciplinary research, which currently has few generally agreed-upon measures with acceptable degrees of accuracy. Researchers at the University of Sussex have begun to address this problem by developing a conceptual framework to gauge research diversity. The current project builds upon that conceptual framework to empirically test metrics that gauge the interdisciplinarity of particular bodies of research. One proposed key measure assesses the degree to which particular research papers, or collections of such, integrate research knowledge from diverse research domains. A second measure determines the degree of specialization of collections of research papers (e.g., those published by a particular research center or those of a research area such as quantum dots). The resulting measures help track and characterize the emergence of new (interdisciplinary) research areas. The project described in this proposal seeks to generate analytical algorithms for indicators of interdisciplinarity. It also seeks to visually depict knowledge interchanges among areas of research activity. Such science maps can help identify and characterize focused areas of research--domains--that are sources of knowledge used by other domains. They can also show the extent of intellectual and social networking among both domains and contributing institutions. This project will, through US-UK collaboration, develop effective means to apply and test these new metrics. The proposed project focuses on nanoscience and nanoengineering ("nano"), an emergent research domain of considerable significance that extends well beyond traditional disciplinary boundaries. Georgia Tech has assembled a substantial nano dataset that will serve as the main testbed for computing and assessing indicator variations. The research team will generate indicator sets and maps of selected nano sub-topics (e.g., molecular motors research). These indicator sets and maps will be shared with researchers and R&D managers to gauge their validity and utility. Taking into account feedback, the research team will then develop a taxonomy of nanotechnology research activity based on identification of coherent research sub-areas.Broader Impacts: These tools better enable scientists, science managers, and Federal science and regulatory agencies to gauge and track cross-domain knowledge transfers. Failure to recognize the full extent and complexity of these patterns could result in major funding and regulatory mistakes. The new indicators and accompanying maps help identify leverage points likely to spark advances in science, technology, and innovation. They can also facilitate graduate education by identifying convergent knowledge domains - potentially emerging "interdisciplines." Better understanding of research landscapes can help orient graduate curricula and spotlight promising dissertation topics. More accurate interdisciplinarity measures also contribute to an ongoing National Academies initiative to bolster interdisciplinary research across the US.

增强科学和创新政策的科学性取决于更好的衡量标准。你无法管理你无法衡量的东西。对于跨学科研究来说尤其如此，目前很少有具有可接受准确度的普遍商定的衡量标准。苏塞克斯大学的研究人员已经开始通过开发一个衡量研究多样性的概念框架来解决这个问题。目前的项目建立在这一概念框架的基础上，对衡量特定研究主体的跨学科程度的指标进行经验测试。一项拟议的关键措施是评估特定的研究论文或此类论文的集合在多大程度上整合了不同研究领域的研究知识。第二个衡量标准确定研究论文集合的专业化程度(例如，由特定研究中心发表的论文或诸如量子点等研究领域的论文)。由此产生的措施有助于跟踪和描述新的(跨学科)研究领域的出现。本提案中所述的项目力求为跨学科指标生成分析算法。它还试图直观地描绘研究活动领域之间的知识交流。这样的科学地图可以帮助确定和描述研究的重点领域--领域--其他领域使用的知识来源。它们还可以显示两个领域和贡献机构之间的智力和社交网络的程度。该项目将通过美英合作，开发有效的方法来应用和测试这些新指标。拟议的项目侧重于纳米科学和纳米工程(“纳米”)，这是一个具有相当重要意义的新兴研究领域，远远超出了传统学科的界限。佐治亚理工学院已经组装了一个大量的纳米数据集，将作为计算和评估指标变化的主要试验台。研究小组将为选定的纳米子主题(例如，分子马达研究)生成指标集和地图。这些指标集和地图将与研究人员和研发经理共享，以衡量其有效性和实用性。考虑到反馈，研究团队将在确定连贯的研究子领域的基础上制定纳米技术研究活动的分类。广泛的影响：这些工具使科学家、科学管理人员以及联邦科学和监管机构能够更好地衡量和跟踪跨领域的知识转移。如果不能充分认识到这些模式的范围和复杂性，可能会导致重大的资金和监管错误。新的指标和附带的地图有助于确定可能引发科学、技术和创新进步的杠杆点。它们还可以通过识别融合的知识领域--潜在地出现的“跨学科”--来促进研究生教育。更好地理解研究背景可以帮助确定研究生课程的方向，并突出有前途的论文主题。更准确的跨学科测量也有助于正在进行的国家科学院倡议，以支持全美的跨学科研究。