  Human creativity is the ultimate driving force behind scientific progress.
While the building blocks of innovations are often embodied in existing
knowledge, it is creativity that blends seemingly disparate ideas. Existing
studies have made striding advances in quantifying creativity of scientific
publications by investigating their citation relationships. Yet, little is
known hitherto about the underlying mechanisms governing scientific creative
processes, largely due to that a paper's references, at best, only partially
reflect its authors' actual information consumption. This work represents an
initial step towards fine-grained understanding of creative processes in
scientific enterprise. In specific, using two web-scale longitudinal datasets
(120.1 million papers and 53.5 billion web requests spanning 4 years), we
directly contrast authors' information consumption behaviors against their
knowledge products. We find that, of 59.0\% papers across all scientific
fields, 25.7\% of their creativity can be readily explained by information
consumed by their authors. Further, by leveraging these findings, we develop a
predictive framework that accurately identifies the most critical knowledge to
fostering target scientific innovations. We believe that our framework is of
fundamental importance to the study of scientific creativity. It promotes
strategies to stimulate and potentially automate creative processes, and
provides insights towards more effective designs of information recommendation
platforms.
