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Article

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

1
Institute of Clinical Epidemiology and Biometry, University of Würzburg, 97080 Würzburg, Germany
2
Institute of Databases and Information Systems, Ulm University, 89081 Ulm, Germany
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Author to whom correspondence should be addressed.
Academic Editors: Ramon Alcarria, Borja Bordel and Eirini Eleni Tsiropoulou
Future Internet 2021, 13(8), 203; https://doi.org/10.3390/fi13080203
Received: 31 May 2021 / Revised: 30 July 2021 / Accepted: 30 July 2021 / Published: 4 August 2021
(This article belongs to the Special Issue Towards Convergence of Internet of Things and Cyber-Physical Systems)
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. View Full-Text
Keywords: system architecture design; bibliometric analysis; community detection system architecture design; bibliometric analysis; community detection
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MDPI and ACS Style

Kammerer, K.; Göster, M.; Reichert, M.; Pryss, R. Ambalytics: A Scalable and Distributed System Architecture Concept for Bibliometric Network Analyses. Future Internet 2021, 13, 203. https://doi.org/10.3390/fi13080203

AMA Style

Kammerer K, Göster M, Reichert M, Pryss R. Ambalytics: A Scalable and Distributed System Architecture Concept for Bibliometric Network Analyses. Future Internet. 2021; 13(8):203. https://doi.org/10.3390/fi13080203

Chicago/Turabian Style

Kammerer, Klaus, Manuel Göster, Manfred Reichert, and Rüdiger Pryss. 2021. "Ambalytics: A Scalable and Distributed System Architecture Concept for Bibliometric Network Analyses" Future Internet 13, no. 8: 203. https://doi.org/10.3390/fi13080203

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