iGEM: a model system for team science and innovation

作     者：Santolini, Marc Blondel, Leo Palmer, Megan J. Ward, Robert N. Jeyaram, Rathin Brink, Kathryn R. Krishna, Abhijeet Barabási, Albert-László 

作者机构：Université Paris Cité Inserm System Engineering and Evolution Dynamics ParisF-75004 France Learning Planet Institute ParisF-75004 France Network Science Institute Department of Physics Northeastern University BostonMA02115 United States Department of Bioengineering Stanford University StanfordCA United States Center for International Security and Cooperation Stanford University StanfordCA United States School of Public Policy Georgia Institute of Technology AtlantaGA United States Channing Division of Network Medicine Department of Medicine Brigham and Women’s Hospital Harvard Medical School BostonMA United States Department of Network and Data Science Central European University Budapest Hungary 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2023年

核心收录：

摘      要：Teams are a primary source of innovation in science and technology. Rather than examining the lone genius, scholarly and policy attention has shifted to understanding how team interactions produce new and useful ideas. Yet the organizational roots of innovation remain unclear, in part because of the limitations of current data. This paper introduces the international Genetically Engineered Machine (iGEM) competition, a model system for studying team science and innovation. By combining digital laboratory notebooks with performance data from 2,406 teams over multiple years of participation, we reveal shared dynamical and organizational patterns across teams and identify features associated with team performance and success. This dataset makes visible organizational behavior that is typically hidden, and thus understudied, creating new opportunities for the science of science and innovation. © 2023, CC BY.