  "Open access" has become a central theme of journal reform in academic
publishing. In this article, I examine the relationship between open access
publishing and an important infrastructural element of a modern research
enterprise, scientific literature text mining, or the use of data analytic
techniques to conduct meta-analyses and investigations into the scientific
corpus. I give a brief history of the open access movement, discuss novel
journalistic practices, and an overview of data-driven investigation of the
scientific corpus. I argue that particularly in an era where the veracity of
many research studies has been called into question, scientific literature text
mining should be one of the key motivations for open access publishing, not
only in the basic sciences, but in the engineering and applied sciences as
well. The enormous benefits of unrestricted access to the research literature
should prompt scholars from all disciplines to lend their vocal support to
enabling legal, wholesale access to the scientific literature as part of a data
science pipeline.
