We begin by discussing what we refer to as the ' informed ' ( or ' critical ' ) view in contrast to Anderson 's popular view ( Sect . 2 ) and explain what we mean by big data and machine learning methods ( Sect . 3 ) . We then elaborate on two paradigmatic uses of big data and machine learning methods in science : skin cancer detection and protein folding ( Sect . 4 ) . On this basis , we develop a taxonomy of expert knowledge that can be applied to big data and machine learning - driven research ( Sect . 5 ) . Finally , we argue that this taxonomy provides a fresh perspective on several debates surrounding the role of big data and machine learning in science : whether they concern inductive methods , the removal of the need for theory , or the constitution of a new scientific paradigm ( Sect . 6 ) .