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Bibliometric indicators in the context of regional repositories: proposing the D-index

Author

Listed:
  • José Osvaldo De Sordi

    (Faculdades Metropolitanas Unidas (FMU))

  • Marco Antonio Conejero

    (Faculdade Campo Limpo Paulista (FACCAMP))

  • Manuel Meireles

    (Faculdade Campo Limpo Paulista (FACCAMP))

Abstract

In collaboration with the managers of a university, we have conducted an action research to gauge the adequacy of texts written by researchers in the doctoral programs of the institution as the input (content) for the university’s distance learning program. For the analyses, bibliometric data were collected regarding the articles in question from the regional SciELO repository. This repository was chosen because the articles are mostly published in Portuguese, which is in the domain of the target readership of the distance learning project. It was observed that there was a need for an indicator that related the number of downloads of an article to the total number of downloads of the journal in which it was published. Thus, we propose the D-index, defined as the number of papers with download number ≥d, as a useful index for characterizing the academic popularity (hits) of a journal. The first applications of the D-index in terms of professional practice were positive, given its usefulness and practicality. The D-index aids the analysis of the download of an article, which is a fundamental event for subsequent reading, internalization and learning. An analysis of this set of actions is essential to the context of regional repositories, as their mission also includes the dissemination of information to aid the learning and education of their readers.

Suggested Citation

  • José Osvaldo De Sordi & Marco Antonio Conejero & Manuel Meireles, 2016. "Bibliometric indicators in the context of regional repositories: proposing the D-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(1), pages 235-258, April.
    • Handle: RePEc:spr:scient:v:107:y:2016:i:1:d:10.1007_s11192-016-1873-x
    DOI: 10.1007/s11192-016-1873-x
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    Cited by:

    1. Bikun Chen, 2018. "Usage pattern comparison of the same scholarly articles between Web of Science (WoS) and Springer," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 519-537, April.
    2. Bikun Chen & Dannan Deng & Zhouyan Zhong & Chengzhi Zhang, 2020. "Exploring linguistic characteristics of highly browsed and downloaded academic articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1769-1790, March.
    3. Muhammad Salman Khan & Muhammad Younas, 2017. "Analyzing readers behavior in downloading articles from IEEE digital library: a study of two selected journals in the field of education," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1523-1537, March.
    4. Guijie Zhang & Luning Liu & Fangfang Wei, 2019. "Key nodes mining in the inventor–author knowledge diffusion network," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 721-735, March.

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