The Center for Science of Science & Innovation (CSSI) is the first center world-wide dedicated to the field of the science of science. The center builds on Kellogg’s long-standing tradition of excellence in this field and helps bring together faculty and students across Kellogg and Northwestern to further and cement our global thought leadership position in the field. A multidisciplinary community by nature, CSSI also serves as the nexus to bring together thought leaders in closely related fields such as computational social science, network science and artificial intelligence.
CSSI collaborators take scientific methods and turn them upon science itself to establish a systematic, quantitative framework that can make sense of mass quantities of data and identify emerging patterns. Armed with big data spanning all phases of scientific production, a defining feature of our work is a mechanistic approach to developing models that can uncover fundamental patterns in science. By combining our diverse expertise and approaches, the results of this center will lead to a qualitative shift in the way knowledge is discovered, science is funded, scientists are trained and nurtured, and excellence is recognized and rewarded.
One of the most universal trends in science and technology today is the growth of large teams in all areas, as solitary researchers and small teams diminish in prevalence.
Members of the CSSI team discuss how today’s practices, policies and resources are still rooted in traditions and intuitions rather than evidence, and why we must work to do better.
Here we find that, for subjects ranging from mobile handsets to automobiles and from smartphone apps to scientific fields, early growth patterns follow a power law with non-integer exponents.
The CSSI team developed a mechanistic model to explore the long-term predictability of citation patterns, the results of which indicate that all papers tend to follow the same universal temporal pattern.
As artificial intelligence (AI) applications see wider deployment, it becomes increasingly important to study the social and societal implications of AI adoption.
An analysis of Web of Science data spanning more than 100 years reveals the rapid growth and increasing multidisciplinarity of physics — as well its internal map of subdisciplines.