A weighted unified informetrics based on Scopus and WoS
Parul Khurana, Geetha Ganesan, Gulshan Kumar, Kiran Sharma

TL;DR
This paper introduces 'conflate', a weighted unified informetrics system that combines data from Scopus and WoS to provide a single, comprehensive metric for publications and citations, enhancing transparency and consistency.
Contribution
The paper proposes a novel weighted unified informetrics system called 'conflate' that integrates multiple databases for more accurate research metrics.
Findings
Conflate provides a unified count of publications and citations from multiple sources.
Comparative analysis shows conflate's metrics differ from individual databases.
Mapping research publications to distributed ledger technology enhances transparency.
Abstract
Numerous indexing databases keep track of the number of publications, citations, etc. in order to maintain the progress of science and individual. However, the choice of journals and articles varies among these indexing databases, hence the number of citations and h-index varies. There is no common platform exists that can provide a single count for the number of publications, citations, h-index, etc. To overcome this limitation, we have proposed a weighted unified informetrics, named "conflate". The proposed system takes into account the input from multiple indexing databases and generates a single output. Here, we have used the data from Scopus and WoS to generate a conflate dataset. Further, a comparative analysis of conflate has been performed with Scopus and WoS at three levels: author, organization, and journal. Finally, a mapping is proposed between research publications and…
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Taxonomy
TopicsAdvanced Text Analysis Techniques · Peer-to-Peer Network Technologies · Semantic Web and Ontologies
