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… Show more
“…An analysis of a set of 110 conferences metadata has been performed to conform to the proposed hypothesis. Several studies, for example Fathalla et al Fathalla et al (2017 and Hiemstra et al Hiemstra et al (2007), have been conducted on analyzing different computer science communities using the metadata of several event series, while Barbosa et al Barbosa et al (2017) have analyzed full papers published in the Brazilian Symposium on Human Factors in Computing Systems (IHC) conference series in the period 1998-2015, Fathalla et al Fathalla et al (2020 have extended their analysis of computer science events metadata to involve scientific events belonging to four fields of science, namely Computer Science, Physics, Engineering, and Mathematics.…”
Section: Related Workmentioning
confidence: 99%
“…In 2020, Fathalla et al Fathalla et al. ( 2020 ) have extended their analysis of computer science events metadata to involve scientific events belonging to four fields of science, namely Computer Science, Physics, Engineering, and Mathematics.…”
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.
“…An analysis of a set of 110 conferences metadata has been performed to conform to the proposed hypothesis. Several studies, for example Fathalla et al Fathalla et al (2017 and Hiemstra et al Hiemstra et al (2007), have been conducted on analyzing different computer science communities using the metadata of several event series, while Barbosa et al Barbosa et al (2017) have analyzed full papers published in the Brazilian Symposium on Human Factors in Computing Systems (IHC) conference series in the period 1998-2015, Fathalla et al Fathalla et al (2020 have extended their analysis of computer science events metadata to involve scientific events belonging to four fields of science, namely Computer Science, Physics, Engineering, and Mathematics.…”
Section: Related Workmentioning
confidence: 99%
“…In 2020, Fathalla et al Fathalla et al. ( 2020 ) have extended their analysis of computer science events metadata to involve scientific events belonging to four fields of science, namely Computer Science, Physics, Engineering, and Mathematics.…”
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.
“…and our previous work (Fathalla et al. 2017a , 2018 , 2020 ; Fathalla and Lange 2017 ) have in common that they lack a systematic, comprehensive definition of quality dimensions and that they focus on just one data source for information about scientific events and therefore only consider such quality metrics that can be computed based on the given data. Fig.…”
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.
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