Using detailed maps of science to identify potential collaborations
Using detailed maps of science to identify potential collaborations
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DOI：
10.1007/s11192-009-0402-6
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发表时间：
2009-04-01
期刊：
影响因子：
3.9
通讯作者：
Boyack, Kevin W.
中科院分区：
文献类型：
--
作者：
Boyack, Kevin W.
近年来，关于科研合作效果的研究不断增多。在机构和国家一级进行了各种研究，许多研究着眼于政策影响。然而，如何为高绩效科学领域的未来合作确定最富有成效的目标的问题尚未得到解决。本文提出了一种确定两个机构之间未来合作目标的方法。该方法的实用性在两个不同的应用程序中显示：确定两个机构之间的作者级别的具体潜在合作，并生成一个指数，可用于战略规划的目的。这些潜在合作的识别是基于找到属于同一个小型论文社区（或论文集群）的作者，使用包含近100万篇论文的科学和技术地图，这些论文被组织成117，435个社区。这里使用的地图也是独一无二的，因为它是第一个将ISI Proceedings数据库与Science和Social Science Indexes结合在一起的地图。
Research on the effects of collaboration in scientific research has been increasing in recent years. A variety of studies have been done at the institution and country level, many with an eye toward policy implications. However, the question of how to identify the most fruitful targets for future collaboration in high-performing areas of science has not been addressed. This paper presents a method for identifying targets for future collaboration between two institutions. The utility of the method is shown in two different applications: identifying specific potential collaborations at the author level between two institutions, and generating an index that can be used for strategic planning purposes. Identification of these potential collaborations is based on finding authors that belong to the same small paper-level community (or cluster of papers), using a map of science and technology containing nearly 1 million papers organized into 117,435 communities. The map used here is also unique in that it is the first map to combine the ISI Proceedings database with the Science and Social Science Indexes at the paper level.