IX.5 复杂性科学的科学地图

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Brian Castellani

Brian Castellani是社会学教授同时也是复杂性科学研究领域的专家,他的地图从宏观水平介绍了1940-2015年期间复杂性科学的学科交叉发展情况。该地图按照大致的时间发展轨迹从左到右进行呈现,包含了五个主要的知识传统:动态系统理论(紫色),系统科学(浅蓝色),复杂系统理论(黄色),控制论(灰色)和人工智能与认知科学(橙色)。环绕在这些知识传统周围的是在复杂性科学中的主要学术主题和方法,即使有的主题被放到不同的发展轨迹上,但主题的颜色与知识传统的颜色相匹配。棕色节点的主题代表特定学科的话题,他们阐明了复杂性科学应用到不同内容中去的途径。双线条连接的主题代表知识传统与新兴领域研究相交叉的主题,如视觉复杂性和基于主体的建模。与这些主题连接的是其奠基者或推动者。自2009年以来,基于持续深入的文献综述、引文分析、专家评审和各领域的研究总结,该地图已经进行了进一步的修改和完善。想要更加深入地了解复杂性科学中的知识传统、研究主题和研究学者,请访问这个地图所在的网址http://www.art-sciencefactory.com/complexity-map.html.

Translation by:

Ying Huang, Yunwei Chen


Castellani, Brian. 2013. Map of Complexity Science. Cleveland, OH. Courtesy of Arts and Science Factory, LLC. In “9th Iteration (2013): Science Maps Showing Trends and Dynamics,” Places & Spaces: Mapping Science, edited by Katy Börner and Todd N. Theriault. http://scimaps.org.

Castellani, Brian. 2013. "Map of the Complexity Sciences." Art and Science Factory. Accessed December 5.1:928-940. Vienna: The Austrian Institute of Technology Press.

Acknowledgements: This exhibit is supported by the National Science Foundation under Grant No. IIS-0238261, CHE-0524661, IIS-0534909 and IIS-0715303, the James S. McDonnell Foundation; Thomson Reuters; the Cyberinfrastructure for Network Science Center, University Information Technology Services, and the School of Library and Information Science, all three at Indiana University. Some of the data used to generate the science maps is from the Web of Science by Thomson Reuters and Scopus by Elsevier. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.