Brian Castellani is a professor of sociology and an expert in the field of complexity studies. His map is a macroscopic, transdisciplinary introduction to the complexity sciences spanning 1940-2015. Moving from left to right, it is read in a roughly historical fashion, evolving along the field’s five major intellectual traditions: dynamical systems theory (purple), systems science (light blue), complex systems theory (yellow), cybernetics (grey), and artificial intelligence and cognitive science (orange). Placed along these traditions are the key scholarly themes and methods used across the complexity sciences. A theme’s color identifies the historical tradition with which it is best associated, even if a theme is placed on a different trajectory. Themes in brown denote discipline-specific topics, which illustrate how the complexity sciences are applied to different content. Double-lined themes denote the intersection of a tradition with a new field of study, as in the case of visual complexity or agent-based modeling. Connected to themes are the scholars who founded or pioneered work in that area. Since 2009, the map has been extensively revised, based on successive, in-depth reviews of the scholarly literature, citation analyses, expert critique, summaries of various areas, and feedback from readers. To take a more in-depth, web-based tour of the traditions, themes, and scholars in the complexity sciences, explore the online version of the map at http://www.art-sciencefactory.com/complexity-map.html.
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.
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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.