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Scholarly event characteristics in four fields of science: a metrics-based analysis

Author

Listed:
  • Said Fathalla

    (University of Bonn
    University of Alexandria)

  • Sahar Vahdati

    (University of Oxford)

  • Christoph Lange

    (RWTH Aachen University
    Fraunhofer FIT)

  • Sören Auer

    (Leibniz University of Hannover
    TIB Leibniz Information Centre for Science and Technology)

Abstract

One of the key channels of scholarly knowledge exchange are scholarly events such as conferences, workshops, symposiums, etc.; such events are especially important and popular in Computer Science, Engineering, and Natural Sciences. However, scholars encounter problems in finding relevant information about upcoming events and statistics on their historic evolution. In order to obtain a better understanding of scholarly event characteristics in four fields of science, we analyzed the metadata of scholarly events of four major fields of science, namely Computer Science, Physics, Engineering, and Mathematics using Scholarly Events Quality Assessment suite, a suite of ten metrics. In particular, we analyzed renowned scholarly events belonging to five sub-fields within Computer Science, namely World Wide Web, Computer Vision, Software Engineering, Data Management, as well as Security and Privacy. This analysis is based on a systematic approach using descriptive statistics as well as exploratory data analysis. The findings are on the one hand interesting to observe the general evolution and success factors of scholarly events; on the other hand, they allow (prospective) event organizers, publishers, and committee members to assess the progress of their event over time and compare it to other events in the same field; and finally, they help researchers to make more informed decisions when selecting suitable venues for presenting their work. Based on these findings, a set of recommendations has been concluded to different stakeholders, involving event organizers, potential authors, proceedings publishers, and sponsors. Our comprehensive dataset of scholarly events of the aforementioned fields is openly available in a semantic format and maintained collaboratively at OpenResearch.org.

Suggested Citation

  • Said Fathalla & Sahar Vahdati & Christoph Lange & Sören Auer, 2020. "Scholarly event characteristics in four fields of science: a metrics-based analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 677-705, May.
    • Handle: RePEc:spr:scient:v:123:y:2020:i:2:d:10.1007_s11192-020-03391-y
    DOI: 10.1007/s11192-020-03391-y
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    References listed on IDEAS

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    Cited by:

    1. Arthur Lackner & Said Fathalla & Mojtaba Nayyeri & Andreas Behrend & Rainer Manthey & Sören Auer & Jens Lehmann & Sahar Vahdati, 2021. "Analysing the evolution of computer science events leveraging a scholarly knowledge graph: a scientometrics study of top-ranked events in the past decade," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 8129-8151, September.
    2. Sahar Vahdati & Said Fathalla & Christoph Lange & Andreas Behrend & Aysegul Say & Zeynep Say & Sören Auer, 2021. "A comprehensive quality assessment framework for scientific events," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 641-682, January.

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