After introducing the concept of compressed sensing as a complementary
measurement mode to the classical Shannon-Nyquist approach, I discuss some of
the drivers, potential challenges and obstacles to its implementation. I end with a
speculative attempt to embed compressed sensing as an enabling methodology
within the emergence of data-driven discovery. As a consequence I predict the
growth of non-nomological sciences where heuristic correlations will find
applications but often bypass conventional pure basic and use-inspired basic
research stages due to the lack of verifiable hypotheses
