作者: Said Fathalla , Sahar Vahdati , Christoph Lange , Sören Auer
DOI: 10.1007/S11192-020-03391-Y
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摘要: One of the key channels scholarly knowledge exchange are events such as conferences, workshops, symposiums, etc.; especially important and popular in Computer Science, Engineering, Natural Sciences. However, scholars encounter problems finding relevant information about upcoming statistics on their historic evolution. In order to obtain a better understanding event characteristics four fields science, we analyzed metadata major namely Physics, Mathematics using Scholarly Events Quality Assessment suite, suite ten metrics. In particular, renowned belonging five sub-fields within World Wide Web, Vision, Software Data Management, well Security Privacy. This analysis is based systematic approach descriptive exploratory data analysis. The findings one hand interesting observe general evolution success factors events; other hand, they allow (prospective) organizers, publishers, committee members assess progress over time compare it same field; finally, help researchers make more informed decisions when selecting suitable venues for presenting work. Based these findings, set recommendations has been concluded different stakeholders, involving potential authors, proceedings sponsors. Our comprehensive dataset aforementioned openly available semantic format maintained collaboratively at OpenResearch.org.