Why IEEE Xplore Matters for Research Trend Analysis in the Energy Sector

Abstract

The paper aims to briefly compare and analyze the results of queries to IEEE Xplore and the leading abstract databases Scopus and Web of Science to identify research trends. Some errors were revealed in the Author Keywords in Web of Science. Therefore, a more detailed analysis that involved comparing various types of key terms was made only for IEEE Xplore and Scopus platforms. The study employed IEEE Access journal metadata as indexed on both platforms. Sample matching for IEEE Xplore and Scopus was achieved by comparing DOI. The IEEE Xplore metadata contains more key term types, which provides an advantage in analyzing research trends. Using NSPEC Controlled Terms from expert-compiled vocabulary provides more stable data, which gives an advantage when considering the change of terms over time. Apriori, an algorithm for finding association rules, was used to compare the co-occurrence of the terms for a more detailed description of sample subjects on both platforms. VOSviewer was used to analyze trends in scientific research based on IEEE Xplore data. The 2011-2021 ten-year period was divided into two sub-intervals for comparing the occurrence of Author Keywords, IEEE Terms, and NSPEC Controlled Terms. Bibliometric data of the IEEE conference proceedings was used to illustrate the importance of context in estimating the growth rate of publishing activity on a topic of interest.

Dataset for bibliometric data-driven research team formation: Case of Politehnica University of Timisoara scholars for the interval 2010–2022

“…Since DBLP records are extremely simple [2] , scholars must identify other bibliometric databases to base their data-driven team formation on. We selected IEEE Xplore to be the data source for two main reasons: the paper metadata structure is very complex, providing adequate information to assess researchers’ technical knowledge and teamwork skills [2] ; and, indexing speed and open access [3] . To the best of our knowledge, the dataset made available in this paper is the first to provide valuable information extracted from a larger spectrum of metadata fields that besides the already mentioned ‘title’, ‘authors’, and ‘year’, also include ‘keywords’, ‘abstract‘, ‘affiliation’, ‘citations count’, or ‘downloads count’.…”