Science of open science: a large scale analysis of team performance in the iGEM scientific competition

Abstract:  For over 10 years, the international Genetically Engineered Machines (iGEM) synthetic biology competition has been encouraging students to work together to solve real-world challenges by building genetically engineered biological systems with standard, inter-changeable parts or BioBricks. Student teams design, build and test their projects over the summer and gather to present their work and compete at the annual Jamboree. A condition of participation to iGEM is that teams document their progress and results on an open wiki website. Given the underlying structure of wikis, it is possible to know which team member has edited which part of the wiki, and at what time. Team also collaborate with one another, forming an international collaboration network. Finally, teams are awarded medals and special prizes (short term impact), and the BioBricks that they engineer can be later re-used by other teams in later years (long term impact). Using retrospective data of 2,000+ teams from over 40 countries, we will present an investigation of what features of team organization (obtained through their wiki) affect team success (medals, prizes etc) in this model of open science. In particular we will show the role of prior experience as well as the importance of scaling (small teams) and organizing (large teams) to meet productivity standards underlying team success. Finally, we will introduce an ongoing study using smartphone-based proximity sensors to quantify at high resolution how team dynamical interaction networks affect team performance in this large-scale distributed context.