Pursuit of scientific discovery is the central underpinning concept of modern civilization. The immense investment in government-sponsored research in the U.S. has laid the foundation for national scientific, economic, and military security in the 21st century. However, the doubling of scientific publications every nine years jeopardizes this foundation because it is becoming increasingly difficult to track the vast majority of relevant research, and hence explore and evaluate relevant information.
For scientists to maintain their awareness of relevant scientific work and continue to make advances in fundamental and applied research, original approaches that utilize newly emerging computational methods and machine-learning capabilities to accelerate scientific progress must be developed.
This tutorial presents novel computational analytic methods capable of unlocking the human knowledge that’s been documented and archived in the unstructured text of hundreds of millions of scientific publications to extend scientific discovery beyond human capacity.
The instructors explore pathways for visualizing and comprehending knowledge propagation, evolution, and assessment of scientific research fronts, and methods for quantifying research impact within the scientific community and beyond.