Details
| Original language | English |
|---|---|
| Pages (from-to) | 8129-8151 |
| Number of pages | 23 |
| Journal | SCIENTOMETRICS |
| Volume | 126 |
| Issue number | 9 |
| Early online date | 10 Jul 2021 |
| Publication status | Published - Sept 2021 |
Abstract
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.
Keywords
- Metadata Analysis, Metric Suite, Ontology, Scholarly Communication, Scientific Events
ASJC Scopus subject areas
- Social Sciences(all)
- Computer Science(all)
- Computer Science Applications
- Social Sciences(all)
- Library and Information Sciences
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In: SCIENTOMETRICS, Vol. 126, No. 9, 09.2021, p. 8129-8151.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Analysing the evolution of computer science events leveraging a scholarly knowledge graph
T2 - a scientometrics study of top-ranked events in the past decade
AU - Lackner, Arthur
AU - Fathalla, Said
AU - Nayyeri, Mojtaba
AU - Behrend, Andreas
AU - Manthey, Rainer
AU - Auer, Sören
AU - Lehmann, Jens
AU - Vahdati, Sahar
PY - 2021/9
Y1 - 2021/9
N2 - 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.
AB - 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.
KW - Metadata Analysis
KW - Metric Suite
KW - Ontology
KW - Scholarly Communication
KW - Scientific Events
UR - http://www.scopus.com/inward/record.url?scp=85110368438&partnerID=8YFLogxK
U2 - 10.1007/s11192-021-04072-0
DO - 10.1007/s11192-021-04072-0
M3 - Article
AN - SCOPUS:85110368438
VL - 126
SP - 8129
EP - 8151
JO - SCIENTOMETRICS
JF - SCIENTOMETRICS
SN - 0138-9130
IS - 9
ER -