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How important is scientific software in bioinformatics research? A comparative study between international and Chinese research communities

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  • Bo Yang
  • Ronald Rousseau
  • Xue Wang
  • Shuiqing Huang

Abstract

Software programs are among the most important tools in data‐driven research. The popularity of well‐known packages and corresponding large numbers of citations received bear testimony of the contribution of scientific software to academic research. Yet software is not generally recognized as an academic outcome. In this study, a usage‐based model is proposed with varied indicators including citations, mentions, and downloads to measure the importance of scientific software. We performed an investigation on a sample of international bioinformatics research articles, and on a sample from the Chinese community. Our analysis shows that scientists in the field of bioinformatics rely heavily on scientific software: the major differences between the international community and the Chinese example being how scientific packages are mentioned in publications and the time gap between the introduction of a package and its use. Biologists publishing in international journals tend to apply the latest tools earlier; Chinese scientists publishing in Chinese tend to follow later. Further, journals with higher impact factors tend to publish articles applying the latest tools earlier.

Suggested Citation

  • Bo Yang & Ronald Rousseau & Xue Wang & Shuiqing Huang, 2018. "How important is scientific software in bioinformatics research? A comparative study between international and Chinese research communities," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(9), pages 1122-1133, September.
    • Handle: RePEc:bla:jinfst:v:69:y:2018:i:9:p:1122-1133
    DOI: 10.1002/asi.24031
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    Citations

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    Cited by:

    1. Robert Tomaszewski, 2023. "Visibility, impact, and applications of bibliometric software tools through citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(7), pages 4007-4028, July.
    2. Enrique Orduña-Malea & Rodrigo Costas, 2021. "Link-based approach to study scientific software usage: the case of VOSviewer," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 8153-8186, September.
    3. Lu Jiang & Xinyu Kang & Shan Huang & Bo Yang, 2022. "A refinement strategy for identification of scientific software from bioinformatics publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3293-3316, June.
    4. Li, Kai & Chen, Pei-Ying & Yan, Erjia, 2019. "Challenges of measuring software impact through citations: An examination of the lme4 R package," Journal of Informetrics, Elsevier, vol. 13(1), pages 449-461.
    5. Yuzhuo Wang & Kai Li, 2024. "How do official software citation formats evolve over time? A longitudinal analysis of R programming language packages," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 3997-4019, July.
    6. Pan, Xuelian & Yan, Erjia & Cui, Ming & Hua, Weina, 2019. "How important is software to library and information science research? A content analysis of full-text publications," Journal of Informetrics, Elsevier, vol. 13(1), pages 397-406.
    7. Wang, Yuzhuo & Zhang, Chengzhi, 2020. "Using the full-text content of academic articles to identify and evaluate algorithm entities in the domain of natural language processing," Journal of Informetrics, Elsevier, vol. 14(4).
    8. Yuzhuo Wang & Chengzhi Zhang & Kai Li, 2022. "A review on method entities in the academic literature: extraction, evaluation, and application," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2479-2520, May.

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