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A comprehensive quality assessment framework for scientific events.

Sahar Vahdati1,2, Said Fathalla3,4, Christoph Lange5,6

  • 1Department of Computer Science, University of Oxford, Oxford, UK.

Scientometrics
|November 10, 2020
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Summary
This summary is machine-generated.

This study introduces a new framework for assessing scientific events, focusing on quality metrics for events, individuals, and bibliometrics. The developed metrics align with community perceptions of top computer science conferences.

Keywords:
BibliometricsMetadata analysisQuality assessmentRecommendationScientific events

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Area of Science:

  • Computer Science
  • Bibliometrics
  • Research Assessment

Background:

  • Systematic assessment of scientific events is crucial for research communities.
  • Existing metrics (e.g., citations, h-index) primarily focus on formal publications, with less investigation into informal venues.
  • Developing assessment metrics is challenging due to diverse community communication rules and quality standards.

Purpose of the Study:

  • To develop a comprehensive framework of assessment metrics for evaluating scientific events and stakeholders.
  • To establish quality metrics across three categories: events, persons, and bibliometrics.
  • To validate the proposed metrics against community consensus on high-quality computer science events.

Main Methods:

  • Developed a framework of assessment metrics for scientific events.
  • Categorized metrics into event-specific, person-specific, and bibliometric measures.
  • Empirically applied the methodology to computer science conferences and workshops using publicly available data.

Main Results:

  • The proposed quality metrics were determined for events, persons, and bibliometrics.
  • Empirical application to computer science events demonstrated the metrics' effectiveness.
  • Metric values correlated with the research community's intuitive agreement on "top conferences".

Conclusions:

  • The developed metrics provide a reliable way to assess the quality of scientific events.
  • Highly-ranked events exhibit common characteristics: outstanding reviews, diverse locations, reputable participants, and renowned sponsors.
  • The framework offers a valuable tool for evaluating scientific events and involved parties.