Tracing Long-Term Outcomes of Basic Research Using Citation Networks.
Tracing Long-Term Outcomes of Basic Research Using Citation Networks.
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DOI：
10.3389/frma.2020.00005
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发表时间：
2020
影响因子：
--
通讯作者：
Aragon R
中科院分区：
文献类型：
--
作者：
Onken J;Miklos AC;Aragon R
近年来，与科学、技术和创新企业相关的数字数据的更大可用性和可访问性促进了科学政策的科学化。从历史上看，这些数据所来源的大多数研究都是计量经济学或“科学计量学”性质的，侧重于开发科学过程的定量数据、模型和指标以及产出和成果。然而，研究影响的更广泛定义需要使用定性案例研究方法。多年来，美国国家卫生研究院等美国联邦科学机构通过追踪记录成功技术开发过程中关键事件的研究，证明了它们支持的研究的影响。这种研究的一个显著缺点和障碍是案例研究方法的劳动密集型性质。然而，目前为支持科学计量学而开发的数据基础设施也可能促进历史追踪研究。在本文中，我们描述了一种方法，我们用来发现长期的，下游的研究成果，在20世纪70年代末和80年代初的支持下，由美国国立卫生研究院的一个组成部分，美国国立综合医学科学研究所。
In recent years, the science of science policy has been facilitated by the greater availability of and access to digital data associated with the science, technology, and innovation enterprise. Historically, most of the studies from which such data are derived have been econometric or “scientometric” in nature, focusing on the development of quantitative data, models, and metrics of the scientific process as well as outputs and outcomes. Broader definitions of research impact, however, necessitate the use of qualitative case-study methods. For many years, U.S. federal science agencies such as the National Institutes of Health have demonstrated the impact of the research they support through tracing studies that document critical events in the development of successful technologies. A significant disadvantage and barrier of such studies is the labor-intensive nature of a case study approach. Currently, however, the same data infrastructures that have been developed to support scientometrics may also facilitate historical tracing studies. In this paper, we describe one approach we used to discover long-term, downstream outcomes of research supported in the late 1970's and early 1980's by the National Institute of General Medical Sciences, a component of the National Institutes of Health.