People involved: Marc Santolini
Keywords: Science of science, collective intelligence, team network, Open science, science of success
With the advent of digital tools to produce and share knowledge, Science is undergoing a deep transition towards a more decentralized and inclusive framework. This transition will be shaped by the integration of machine learning and artificial intelligence, allowing to build efficient recommendation systems and find needles in a stack of massive amounts of open knowledge through designed serendipity. For such a design to operate as efficiently, transparently and ethically as possible, scientists need to turn the microscope on themselves and understand the scientific process itself. This endeavour, which has for long been the realm of the philosophy of science, has recently gathered a new crowd of physicists, mathematicians, statisticians or social scientists: this is the advent of the Science of Science. Researchers are linked by co-authorships, ideas by citations, research institutions by collaborations, forming networks at various scales that underlie the scientific process. Such networks are not only a convenient description, they are also predictive of the success or percolation of an idea, a paper, a collaboration. In this project, we aim to dissect Science further and understand its underpinnings in situ by using the iGEM scientific competition as a “model organism”. For more than 10 years, 2000+ participating student teams (from high school to graduate) have worked during the summer on synthetic biology projects and have been awarded medals and prizes. Each team documents their work in an open Lab Notebook, allowing to capture features that associate with their end success. While this offers insights on the process of doing science, it remains a virtual footprint of complex real-world interactions. Here, we will overcome this issue by following the face-to-face interactions in the lab for a significant number of teams through discreet sensors. This will offer unprecedented measurements of the dynamical processes underlying the making of science, exhibiting the anatomy of Science in the making to better understand and design its transition.