  We stand at the foot of a significant inflection in the trajectory of
scientific discovery. As society continues on its fast-paced digital
transformation, so does humankind's collective scientific knowledge and
discourse. We now read and write papers in digitized form, and a great deal of
the formal and informal processes of science are captured digitally --
including papers, preprints and books, code and datasets, conference
presentations, and interactions in social networks and collaboration and
communication platforms. The transition has led to the creation and growth of a
tremendous amount of information -- much of which is available for public
access -- opening exciting opportunities for computational models and systems
that analyze and harness it. In parallel, exponential growth in data processing
power has fueled remarkable advances in artificial intelligence, including
large neural language models capable of learning powerful representations from
unstructured text. Dramatic changes in scientific communication -- such as the
advent of the first scientific journal in the 17th century -- have historically
catalyzed revolutions in scientific thought. The confluence of societal and
computational trends suggests that computer science is poised to ignite a
revolution in the scientific process itself.
