![]() SciSci has revealed choices and trade-offs that scientists face as they advance both their own careers and the scientific horizon. Microscopic models have traced the dynamics of citation accumulation, allowing us to predict the future impact of individual papers. This representation has unveiled patterns characterizing the emergence of new scientific fields through the study of collaboration networks and the path of impactful discoveries through the study of citation networks. Science can be described as a complex, self-organizing, and evolving network of scholars, projects, papers, and ideas. The value proposition of SciSci is that with a deeper understanding of the factors that drive successful science, we can more effectively address environmental, societal, and technological problems. In the past decade, SciSci has benefited from an influx of natural, computational, and social scientists who together have developed big data–based capabilities for empirical analysis and generative modeling that capture the unfolding of science, its institutions, and its workforce. The science of science (SciSci) offers a quantitative understanding of the interactions among scientific agents across diverse geographic and temporal scales: It provides insights into the conditions underlying creativity and the genesis of scientific discovery, with the ultimate goal of developing tools and policies that have the potential to accelerate science. The increasing availability of digital data on scholarly inputs and outputs-from research funding, productivity, and collaboration to paper citations and scientist mobility-offers unprecedented opportunities to explore the structure and evolution of science.
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