Four decades of data & knowledge engineering: A bibliometric analysis and topic evolution study (1985–2024)

Abstract

The Data and Knowledge Engineering (DKE) journal has established a significant global research presence over four decades, substantially contributing to the advancement of data and knowledge engineering disciplines. This comprehensive bibliometric study analyzes the journal’s publications over the past 40 years (1985–2024), employing bibliographic records and citation data from Scopus, Web of Science (WoS), and ScienceDirect. By utilizing CiteSpace for citation and co-citation mapping and Dirichlet Multinomial Regression (DMR) topic modeling for trend analysis, the research provides a multifaceted examination of the journal’s scholarly landscape. Over its 40-year history, DKE has published 1951 articles, accumulating 53,594 citations. The study comprehensively explores key bibliometric dimensions, including influential authors, author networks, citation patterns, topic clusters, institutional contributions, and research funding sponsors, as well as evolution of topics, showing increasing, decreasing, or constant trends. Comprehensive analysis offers a meta-analytical perspective on DKE’s scholarly contributions, positioning the journal as a pioneering publication platform that advances critical knowledge and methodological innovations in data and knowledge engineering research domains. Through an in-depth examination of the journal’s publication trajectory, the study provides insights into the field’s scholarly evolution, highlighting DKE’s pivotal role in shaping academic discourse and technological understanding.