iGEM: a model system for team science and innovation

TL;DR

This paper presents iGEM as a comprehensive model system for studying team science and innovation, utilizing extensive data to uncover organizational patterns linked to successful scientific team performance.

Contribution

It introduces a novel dataset combining digital notebooks and performance metrics from thousands of teams, enabling analysis of organizational behaviors influencing innovation.

Findings

Shared dynamical patterns across teams

Organizational features linked to success

New insights into team performance dynamics

Abstract

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.