25 years of knowledge and information systems: a bibliometric retrospective

Abstract In 2025, Knowledge and Information Systems (KAIS) celebrates its 25th anniversary. To mark this occasion, this study presents a comprehensive bibliometric analysis covering the period 1999–2024, examining publication and citation patterns, influential authors, institutions, countries, and evolving research themes. Drawing on data from the Web of Science (WoS) Core Collection, the analysis integrates classical bibliometric indicators with science mapping techniques, including co-citation, bibliographic coupling, and keyword co-occurrence, supported by VOSviewer and Bibliometrix tools. The findings reveal that KAIS has published 2,385 articles, which have collectively received 54,319 citations, demonstrating sustained global influence. The journal’s intellectual core remains grounded in data mining, classification, clustering, and machine learning, while emerging themes—such as deep learning, graph neural networks, natural language processing, and concept drift—reflect its adaptation to contemporary developments in artificial intelligence. China and the United States lead in both productivity and impact, illustrating the globalization of the KAIS research community. This study offers insights into the evolution of knowledge and information systems as an interdisciplinary field, emphasizing KAIS’s dual role in preserving methodological rigor and promoting innovation. Overall, the journal stands as a benchmark for studying the dynamics of data-driven, intelligent, and responsible knowledge discovery.

Authors

Institutions

Publication Details

Journal
Knowledge and Information Systems
Published
2026-05-23
DOI
https://doi.org/10.1007/s10115-026-02739-9
Primary Topic
Advanced Graph Neural Networks
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

25 years of knowledge and information systems: a bibliometric retrospective

Jose M Merigo, Ana M. Gil-Lafuente, Luciano Barcellos-Paula
Knowledge and Information Systems
Advanced Graph Neural Networks
article

25 years of knowledge and information systems: a bibliometric retrospective

Jose M Merigo, Ana M. Gil-Lafuente, Luciano Barcellos-Paula
article en

Abstract

Abstract In 2025, Knowledge and Information Systems (KAIS) celebrates its 25th anniversary. To mark this occasion, this study presents a comprehensive bibliometric analysis covering the period 1999–2024, examining publication and citation patterns, influential authors, institutions, countries, and evolving research themes. Drawing on data from the Web of Science (WoS) Core Collection, the analysis integrates classical bibliometric indicators with science mapping techniques, including co-citation, bibliographic coupling, and keyword co-occurrence, supported by VOSviewer and Bibliometrix tools. The findings reveal that KAIS has published 2,385 articles, which have collectively received 54,319 citations, demonstrating sustained global influence. The journal’s intellectual core remains grounded in data mining, classification, clustering, and machine learning, while emerging themes—such as deep learning, graph neural networks, natural language processing, and concept drift—reflect its adaptation to contemporary developments in artificial intelligence. China and the United States lead in both productivity and impact, illustrating the globalization of the KAIS research community. This study offers insights into the evolution of knowledge and information systems as an interdisciplinary field, emphasizing KAIS’s dual role in preserving methodological rigor and promoting innovation. Overall, the journal stands as a benchmark for studying the dynamics of data-driven, intelligent, and responsible knowledge discovery.

Knowledge and Information SystemsVol. 68(1)
University of Technology Sydney (AU), Pontificia Universidad Católica del Perú (PE), Universitat de Barcelona (ES)
University of Technology Sydney
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Advanced Graph Neural Networks
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.