A comprehensive quality assessment framework for scientific events

2021
Systematic assessment of scientific events has become increasingly important for research communities. A range of metrics (e.g., citations, h-index) have been developed by different research communities to make such assessments effectual. However, most of the metrics for assessing the quality of less formal publication venues and events have not yet deeply investigated. It is also rather challenging to develop respective metrics because each research community has its own formal and informal rules of communication and quality standards. In this article, we develop a comprehensive framework of assessment metrics for evaluating scientific events and involved stakeholders. The resulting quality metrics are determined with respect to three general categories-events, persons, and bibliometrics. Our assessment methodology is empirically applied to several series of computer science events, such as conferences and workshops, using publicly available data for determining quality metrics. We show that the metrics' values coincide with the intuitive agreement of the community on its top conferences. Our results demonstrate that highly-ranked events share similar profiles, including the provision of outstanding reviews, visiting diverse locations, having reputed people involved, and renowned sponsors.
SCIENTOMETRICS
页码:641-682|卷号:126|期号:1
ISSN:0138-9130
收录类型
SSCI
发表日期
2021
学科领域
循证社会科学-综合
国家
英国
语种
英语
DOI
10.1007/s11192-020-03758-1
其他关键词
SEMANTIC PUBLISHING CHALLENGE; ARTICLES
EISSN
1588-2861
资助机构
DFGGerman Research Foundation (DFG)European Commission [LA 3745/4-1]; ERCEuropean Research Council (ERC)European Commission [819536]; Projekt DEAL
资助信息
Open Access funding enabled and organized by Projekt DEAL. This work is part of the doctoral dissertation of the first author at the University of Bonn, and has been partially presented in Chapter 4 of the dissertation documentation (Vahdati 2019). The work as been partially funded by DFG under grant agreement LA 3745/4-1 (ConfIDent) and ERC project ScienceGRAPH No. 819536. The authors would like to thank Prof. Maria-Esther Vidal for her valuable comments during the development of this work.
被引频次(WOS)
2
被引更新日期
2022-01
来源机构
University of Oxford University of Bonn Egyptian Knowledge Bank (EKB) Alexandria University RWTH Aachen University Fraunhofer Gesellschaft Fraunhofer Institute Center Schloss Birlinghoven University of Hannover
关键词
Recommendation Scientific events Quality assessment Metadata analysis Bibliometrics