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Scientific Literature Text Mining and the Case for Open Access

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  • Sarma, Gopal P.

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.

Suggested Citation

  • Sarma, Gopal P., 2017. "Scientific Literature Text Mining and the Case for Open Access," OSF Preprints n6zqn_v1, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:n6zqn_v1
    DOI: 10.31219/osf.io/n6zqn_v1
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    References listed on IDEAS

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    1. Ding, Ying & Liu, Xiaozhong & Guo, Chun & Cronin, Blaise, 2013. "The distribution of references across texts: Some implications for citation analysis," Journal of Informetrics, Elsevier, vol. 7(3), pages 583-592.
    2. Ying Ding, 2011. "Applying weighted PageRank to author citation networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(2), pages 236-245, February.
    3. Ying Ding, 2011. "Topic‐based PageRank on author cocitation networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(3), pages 449-466, March.
    4. Wenjia Zhu & Jiancheng Guan, 2013. "A bibliometric study of service innovation research: based on complex network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1195-1216, March.
    5. Xiaodan Zhu & Peter Turney & Daniel Lemire & André Vellino, 2015. "Measuring academic influence: Not all citations are equal," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(2), pages 408-427, February.
    6. Erika Check & David Cyranoski, 2005. "Korean scandal will have global fallout," Nature, Nature, vol. 438(7071), pages 1056-1057, December.
    7. Ying Ding, 2011. "Applying weighted PageRank to author citation networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(2), pages 236-245, February.
    8. Ying Ding, 2011. "Topic-based PageRank on author cocitation networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(3), pages 449-466, March.
    9. Min Song & SuYeon Kim & Guo Zhang & Ying Ding & Tamy Chambers, 2014. "Productivity and influence in bioinformatics: A bibliometric analysis using PubMed central," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(2), pages 352-371, February.
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