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Sidiq, M., Hanafi, I., & Ekaputra, F. J. (2020). SEforRA: A Bibliometrics-ready Academic Digital Library Search Engine Alternative. KnE Social Sciences, 4(14), 206–218. https://doi.org/10.18502/kss.v4i14.7877

https://doi.org/10.18502/kss.v4i14.7877

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authors

  • Muhaemin Sidiq

    Muhaemin Sidiq

    Educational Technology Doctorate Program, Universitas Negeri Jakarta, Indonesia
  • Ivan Hanafi

    Ivan Hanafi

    Vocational Education Program, Universitas Negeri Jakarta, Indonesia
  • Fajar J. Ekaputra

    Fajar J. Ekaputra

    Institute of Systems Engineering, Faculty of Informatics - TU Wien, Austria

Published Date

  • Nov 11, 2020

SEforRA: A Bibliometrics-ready Academic Digital Library Search Engine Alternative

KnE Social Sciences / International Conference on Humanities, Education and Social Sciences (IC-HEDS) 2019 / Pages 206–218

Abstract

Naturally, not all researchers can develop their own software to search for academic publications from digital libraries. Nevertheless, at several stages of their research, they will need to search digital libraries for relevant scientific publications and bibliometric information. There are typically two approaches used by researchers to search for scientific publications: (i) using Google Scholar search, or (ii) using publication metadata available from several sources, such as CrossRef and publishers. However, in developing countries like Indonesia, neither option provided users with complete information, since (i) Google Scholar does not provide bibliometric details, and (ii) complete bibliometric information from other sources is often not available due to incomplete data (e.g., CrossRef) or the necessity to pay a subscription fee (e.g., Springer and Elsevier). The development of Search Engine for Research Articles (SEforRA) is a solution to this issue which provides researchers with bibliometricready publication metadata. SEforRA extracts and processes data from CrossRef, publishers, and other sources to provide an integrated platform for researchers to search and retrieve publication metadata, which is ready to use further in their research.



Keywords: search engine for research articles, academic search engines, text data mining, bibliometrics

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