Details
| Original language | English |
|---|---|
| Pages (from-to) | 677-705 |
| Number of pages | 29 |
| Journal | SCIENTOMETRICS |
| Volume | 123 |
| Issue number | 2 |
| Early online date | 28 Feb 2020 |
| Publication status | Published - May 2020 |
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 of four major fields of science, namely Computer Science, Physics, Engineering, and Mathematics using Scholarly Events Quality Assessment suite, a suite of ten metrics.In particular, we analyzed renowned scholarly events belonging to five sub-fields within Computer Science, namely World Wide Web, Computer Vision, Software Engineering, Data Management, as well as Security and Privacy.This analysis is based on a systematic approach using descriptive statistics as well as exploratory data analysis. The findings are on the one hand interesting to observe the general evolution and success factors of scholarly events; on the other hand, they allow (prospective) event organizers, publishers, and committee members to assess the progress of their event over time and compare it to other events in the same field; and finally, they help researchers to make more informed decisions when selecting suitable venues for presenting their work.Based on these findings, a set of recommendations has been concluded to different stakeholders, involving event organizers, potential authors, proceedings publishers, and sponsors. Our comprehensive dataset of scholarly events of the aforementioned fields is openly available in a semantic format and maintained collaboratively at OpenResearch.org.
Keywords
- Scholarly events, Metadata analysis, Scholarly communication, Publishing paradigms, Metrics suite, OpenResearch.org
ASJC Scopus subject areas
- Social Sciences(all)
- Social Sciences(all)
- Library and Information Sciences
- Computer Science(all)
- Computer Science Applications
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In: SCIENTOMETRICS, Vol. 123, No. 2, 05.2020, p. 677-705.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Scholarly event characteristics in four fields of science
T2 - a metrics-based analysis
AU - Fathalla, Said
AU - Vahdati, Sahar
AU - Lange, Christoph
AU - Auer, Sören
N1 - Funding information: Open Access funding provided by Projekt DEAL. Part of this work has been funded by the DFG project “ConfIDent – A reliable platform for scientific events” (Grant agreements LA 3745/4-1 and SE 1827/16-1) as well as ERC ScienceGRAPH (Grant Agreement ID 819536).
PY - 2020/5
Y1 - 2020/5
N2 - 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 of four major fields of science, namely Computer Science, Physics, Engineering, and Mathematics using Scholarly Events Quality Assessment suite, a suite of ten metrics.In particular, we analyzed renowned scholarly events belonging to five sub-fields within Computer Science, namely World Wide Web, Computer Vision, Software Engineering, Data Management, as well as Security and Privacy.This analysis is based on a systematic approach using descriptive statistics as well as exploratory data analysis. The findings are on the one hand interesting to observe the general evolution and success factors of scholarly events; on the other hand, they allow (prospective) event organizers, publishers, and committee members to assess the progress of their event over time and compare it to other events in the same field; and finally, they help researchers to make more informed decisions when selecting suitable venues for presenting their work.Based on these findings, a set of recommendations has been concluded to different stakeholders, involving event organizers, potential authors, proceedings publishers, and sponsors. Our comprehensive dataset of scholarly events of the aforementioned fields is openly available in a semantic format and maintained collaboratively at OpenResearch.org.
AB - 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 of four major fields of science, namely Computer Science, Physics, Engineering, and Mathematics using Scholarly Events Quality Assessment suite, a suite of ten metrics.In particular, we analyzed renowned scholarly events belonging to five sub-fields within Computer Science, namely World Wide Web, Computer Vision, Software Engineering, Data Management, as well as Security and Privacy.This analysis is based on a systematic approach using descriptive statistics as well as exploratory data analysis. The findings are on the one hand interesting to observe the general evolution and success factors of scholarly events; on the other hand, they allow (prospective) event organizers, publishers, and committee members to assess the progress of their event over time and compare it to other events in the same field; and finally, they help researchers to make more informed decisions when selecting suitable venues for presenting their work.Based on these findings, a set of recommendations has been concluded to different stakeholders, involving event organizers, potential authors, proceedings publishers, and sponsors. Our comprehensive dataset of scholarly events of the aforementioned fields is openly available in a semantic format and maintained collaboratively at OpenResearch.org.
KW - Scholarly events
KW - Metadata analysis
KW - Scholarly communication
KW - Publishing paradigms
KW - Metrics suite
KW - OpenResearch.org
UR - http://www.scopus.com/inward/record.url?scp=85083954730&partnerID=8YFLogxK
U2 - 10.1007/s11192-020-03391-y
DO - 10.1007/s11192-020-03391-y
M3 - Article
VL - 123
SP - 677
EP - 705
JO - SCIENTOMETRICS
JF - SCIENTOMETRICS
SN - 0138-9130
IS - 2
ER -