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Ambalytics: A Scalable and Distributed System Architecture Concept for Bibliometric Network Analyses

Author

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  • Klaus Kammerer

    (Institute of Clinical Epidemiology and Biometry, University of Würzburg, 97080 Würzburg, Germany)

  • Manuel Göster

    (Institute of Clinical Epidemiology and Biometry, University of Würzburg, 97080 Würzburg, Germany)

  • Manfred Reichert

    (Institute of Databases and Information Systems, Ulm University, 89081 Ulm, Germany)

  • Rüdiger Pryss

    (Institute of Clinical Epidemiology and Biometry, University of Würzburg, 97080 Würzburg, Germany)

Abstract

A deep understanding about a field of research is valuable for academic researchers. In addition to technical knowledge, this includes knowledge about subareas, open research questions, and social communities (networks) of individuals and organizations within a given field. With bibliometric analyses, researchers can acquire quantitatively valuable knowledge about a research area by using bibliographic information on academic publications provided by bibliographic data providers. Bibliometric analyses include the calculation of bibliometric networks to describe affiliations or similarities of bibliometric entities (e.g., authors) and group them into clusters representing subareas or communities. Calculating and visualizing bibliometric networks is a nontrivial and time-consuming data science task that requires highly skilled individuals. In addition to domain knowledge, researchers must often provide statistical knowledge and programming skills or use software tools having limited functionality and usability. In this paper, we present the ambalytics bibliometric platform, which reduces the complexity of bibliometric network analysis and the visualization of results. It accompanies users through the process of bibliometric analysis and eliminates the need for individuals to have programming skills and statistical knowledge, while preserving advanced functionality, such as algorithm parameterization, for experts. As a proof-of-concept, and as an example of bibliometric analyses outcomes, the calculation of research fronts networks based on a hybrid similarity approach is shown. Being designed to scale, ambalytics makes use of distributed systems concepts and technologies. It is based on the microservice architecture concept and uses the Kubernetes framework for orchestration. This paper presents the initial building block of a comprehensive bibliometric analysis platform called ambalytics, which aims at a high usability for users as well as scalability.

Suggested Citation

  • Klaus Kammerer & Manuel Göster & Manfred Reichert & Rüdiger Pryss, 2021. "Ambalytics: A Scalable and Distributed System Architecture Concept for Bibliometric Network Analyses," Future Internet, MDPI, vol. 13(8), pages 1-29, August.
    • Handle: RePEc:gam:jftint:v:13:y:2021:i:8:p:203-:d:607873
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    References listed on IDEAS

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    1. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    2. M.J. Cobo & A.G. López‐Herrera & E. Herrera‐Viedma & F. Herrera, 2011. "Science mapping software tools: Review, analysis, and cooperative study among tools," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(7), pages 1382-1402, July.
    3. van Eck, Nees Jan & Waltman, Ludo, 2014. "CitNetExplorer: A new software tool for analyzing and visualizing citation networks," Journal of Informetrics, Elsevier, vol. 8(4), pages 802-823.
    4. Fabian Meyer-Brötz & Edgar Schiebel & Leo Brecht, 2017. "Experimental evaluation of parameter settings in calculation of hybrid similarities: effects of first- and second-order similarity, edge cutting, and weighting factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1307-1325, June.
    5. Sebastian Grauwin & Pablo Jensen, 2011. "Mapping scientific institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(3), pages 943-954, December.
    6. Ole Ellegaard & Johan A. Wallin, 2015. "The bibliometric analysis of scholarly production: How great is the impact?," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1809-1831, December.
    7. M.J. Cobo & A.G. López-Herrera & E. Herrera-Viedma & F. Herrera, 2011. "Science mapping software tools: Review, analysis, and cooperative study among tools," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(7), pages 1382-1402, July.
    8. Sven E. Hug & Michael Ochsner & Martin P. Brändle, 2017. "Citation analysis with microsoft academic," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 371-378, April.
    9. M.J. Cobo & A.G. López-Herrera & E. Herrera-Viedma & F. Herrera, 2012. "SciMAT: A new science mapping analysis software tool," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(8), pages 1609-1630, August.
    10. McLevey, John & McIlroy-Young, Reid, 2017. "Introducing metaknowledge: Software for computational research in information science, network analysis, and science of science," Journal of Informetrics, Elsevier, vol. 11(1), pages 176-197.
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    1. Xingrong Guo & Yiming Guo & Yunqin Liu, 2021. "The Development of Extended Reality in Education: Inspiration from the Research Literature," Sustainability, MDPI, vol. 13(24), pages 1-20, December.

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