Scientific literature text mining and the case for Open Access

School of Medicine, Emory University, Atlanta, Georgia, United States
Subject Areas
Bioinformatics, Evidence Based Medicine, Health Policy, Translational Medicine, Science Policy
reproducibility crisis, open access, scientific data science, meta-analysis, journal reform, altmetrics, peer review, preprints, scientific epistemology, structure of science
© 2018 Sarma
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Sarma GP. 2018. Scientific literature text mining and the case for Open Access. PeerJ Preprints 6:e2566v2


“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.

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