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

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autorschaft

Organisationseinheiten

Externe Organisationen

  • Rheinische Friedrich-Wilhelms-Universität Bonn
  • Alexandria University
  • University of Oxford
  • Rheinisch-Westfälische Technische Hochschule Aachen (RWTH)
  • Fraunhofer-Institut für Angewandte Informationstechnik (FIT)
  • Technische Informationsbibliothek (TIB) Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek

Details

OriginalspracheEnglisch
Seiten (von - bis)677-705
Seitenumfang29
FachzeitschriftSCIENTOMETRICS
Jahrgang123
Ausgabenummer2
Frühes Online-Datum28 Feb. 2020
PublikationsstatusVeröffentlicht - Mai 2020

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.

ASJC Scopus Sachgebiete

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Scholarly event characteristics in four fields of science: a metrics-based analysis. / Fathalla, Said; Vahdati, Sahar; Lange, Christoph et al.
in: SCIENTOMETRICS, Jahrgang 123, Nr. 2, 05.2020, S. 677-705.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Fathalla S, Vahdati S, Lange C, Auer S. Scholarly event characteristics in four fields of science: a metrics-based analysis. SCIENTOMETRICS. 2020 Mai;123(2):677-705. Epub 2020 Feb 28. doi: 10.1007/s11192-020-03391-y
Fathalla, Said ; Vahdati, Sahar ; Lange, Christoph et al. / Scholarly event characteristics in four fields of science : a metrics-based analysis. in: SCIENTOMETRICS. 2020 ; Jahrgang 123, Nr. 2. S. 677-705.
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title = "Scholarly event characteristics in four fields of science: a metrics-based analysis",
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.",
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N1 - Funding information: Open Access funding provided by Projekt DEAL. Part of this work has been funded by the DFG project “ConfIDent – A reliable platform for scientific events” (Grant agreements LA 3745/4-1 and SE 1827/16-1) as well as ERC ScienceGRAPH (Grant Agreement ID 819536).

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