Scientific Literature Text Mining and the Case for Open Access

TL;DR

Open access publishing is crucial for enabling scientific literature text mining, which enhances research integrity and cross-disciplinary investigations by providing unrestricted access to scientific data and facilitating advanced data analysis techniques.

Contribution

The paper highlights the importance of open access for scientific literature text mining and advocates for legal, unrestricted access to support data-driven research across disciplines.

Findings

Open access facilitates data-driven investigations of scientific literature.

Text mining enhances meta-analyses and research verification.

Open access supports transparency and reproducibility in science.

Abstract

"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.