The publish or perish culture of scholarly communication results in quality and relevance to be are subordinate to quantity. Scientific events such as conferences play an important role in scholarly communication and knowledge exchange. Researchers in many fields, such as computer science, often need to search for events to publish their research results, establish connections for collaborations with other researchers and stay up to date with recent works. Researchers need to have a meta-research understanding of the quality of scientific events to publish in high-quality venues. However, there are many diverse and complex criteria to be explored for the evaluation of events. Thus, finding events with quality-related criteria becomes a time-consuming task for researchers and often results in an experience-based subjective evaluation. OpenResearch.org is a crowd-sourcing platform that provides features to explore previous and upcoming events of computer science, based on a knowledge graph. In this paper, we devise an ontology representing scientific events metadata. Furthermore, we introduce an analytical study of the evolution of Computer Science events leveraging the OpenResearch.org knowledge graph. We identify common characteristics of these events, formalize them, and combine them as a group of metrics. These metrics can be used by potential authors to identify high-quality events. On top of the improved ontology, we analyzed the metadata of renowned conferences in various computer science communities, such as VLDB, ISWC, ESWC, WIMS, and SEMANTiCS, in order to inspect their potential as event metrics.

学术交流的出版或消亡文化导致质量和相关性从属于数量。会议等科学活动在学术交流和知识交流中发挥着重要作用。许多领域的研究人员，例如计算机科学，经常需要搜索事件以发布他们的研究结果，建立与其他研究人员合作的联系，并及时了解最近的工作。研究人员需要对科学事件的质量有元研究的理解，才能在高质量的场所发表。然而，对于事件的评估，有许多不同且复杂的标准有待探索。因此，寻找具有质量相关标准的事件对于研究人员来说是一项耗时的任务，并且通常会导致基于经验的主观评估。开放研究。org 是一个众包平台，它提供基于知识图谱探索计算机科学先前和即将发生的事件的功能。在本文中，我们设计了一个表示科学事件元数据的本体。此外，我们利用 OpenResearch.org 知识图谱介绍了对计算机科学事件演变的分析研究。我们识别这些事件的共同特征，将它们形式化，并将它们组合为一组指标。潜在作者可以使用这些指标来识别高质量的事件。在改进的本体之上，我们分析了各种计算机科学社区中著名会议的元数据，例如 VLDB、ISWC、ESWC、WIMS 和 SEMANTiCS，以检查它们作为事件指标的潜力。