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| Empirical Study of Knowledge Association Methods for Major Scientific Discoveries |
| Ren Xiaoya1,2, Zhang Zhiqiang1,3 |
1.National Science Library (Chengdu), Chinese Academy of Sciences, Chengdu 610299
2.National Science Library, Chinese Academy of Sciences, Beijing 100190
3.Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 |
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Abstract Scientific discovery is that of “undiscovered discoveries,” and major scientific discoveries can promote the exploration and development of science. The emergence of scientific discovery is a complex phenomenon, and scientific knowledge is embedded therein. However, owing to the proliferation of information; limitations of knowledge; and artificial removal, concealment, or weakening, more undiscovered implicit relationships between scientific discoveries exist. Therefore, we present a knowledge association method of scientific discoveries that combines multiple citation relations to determine the knowledge-based associations between major scientific discoveries from a deeper granularity and a more diverse perspective. We adopt the Fields Medal, Lasker Award, and Turing Award as the empirical research objects. Quantitative and time series analyses are used to explore the knowledge dissemination regularities and characteristics of scientific discovery between various fields from the perspective of backtracking, combined with a qualitative interpretation of scientific discoveries and expert consultation. Finally, we refine the knowledge dissemination patterns of scientific discovery. Our results reveal five types of knowledge dissemination patterns between scientific discoveries: linear (simple and closed linear), bridge, radial, and multiple. Our empirical findings could deepen researchers’ understanding of the regularities of scientific discoveries and provide a reference for policy formulation in research funding and scientific evaluation.
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Received: 13 September 2022
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