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.

中文翻译：

---

科学事件的综合质量评估框架

对科学事件的系统评估对于研究界变得越来越重要。不同的研究团体已经开发了一系列指标（例如，引文、h 指数）以使此类评估有效。然而，用于评估不太正式的出版场所和活动质量的大多数指标尚未深入研究。制定各自的指标也相当具有挑战性，因为每个研究团体都有自己的正式和非正式的沟通规则和质量标准。在本文中，我们开发了一个综合评估指标框架，用于评估科学事件和相关利益相关者。由此产生的质量指标是根据三个一般类别确定的——事件、人员和文献计量。我们的评估方法经验性地应用于多个系列的计算机科学活动，例如会议和研讨会，使用公开可用的数据来确定质量指标。我们表明，这些指标的值与社区对其“顶级会议”的直觉一致。我们的结果表明，排名靠前的活动具有相似的概况，包括提供出色的评论、访问不同的地点、参与的知名人士和知名赞助商。