Data and knowledge engineering: Insights from forty years of publication

IF 2.7 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Data & Knowledge Engineering Pub Date : 2025-07-17 DOI:10.1016/j.datak.2025.102492

Jacky Akoka , Isabelle Comyn-Wattiau , Nicolas Prat , Veda C. Storey

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引用次数: 0

Abstract

The journal, Data and Knowledge Engineering (DKE), first published by Elsevier in 1985, has now been in existence for forty years. This journal has evolved and matured to play an important role in establishing and progressing research on conceptual modeling and related areas. To accurately characterize the history and current state of the research contributions and their impact, we analyze its publications in three phases, by employing bibliometric techniques of co-citation, bibliographic coupling, main path analysis, and topic modeling. Using descriptive bibliometrics, the results from the first phase provide an overview of the articles that have been published in the journal. It analyzes the dynamics and trend patterns of publications, specifically, their main topics and contributions. Using bibliometric mapping, the second phase identifies the journal's intellectual structure, its primary research themes, and the pathways through which knowledge is disseminated between the most influential articles. The third phase entails a comparison of DKE with other scientific journals that share at least some of its scope. In addition to delineating the strengths of DKE, we provide insights into how DKE might continue to evolve and progress the contributions to the field.

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数据和知识工程：来自出版四十年的见解

《数据与知识工程》（DKE）杂志于1985年由爱思唯尔首次出版，至今已有40年的历史。这本杂志已经发展和成熟，在建立和推进概念建模和相关领域的研究方面发挥了重要作用。为了准确地描述研究贡献的历史和现状及其影响，我们采用共被引、书目耦合、主路径分析和主题建模等文献计量技术，分三个阶段对其出版物进行了分析。使用描述性文献计量学，第一阶段的结果提供了在期刊上发表的文章的概述。它分析了出版物的动态和趋势模式，特别是它们的主要主题和贡献。第二阶段使用文献计量图，确定期刊的知识结构、主要研究主题，以及在最具影响力的文章之间传播知识的途径。第三阶段需要将DKE与其他科学期刊进行比较，这些期刊至少有一部分共享它的范围。除了描述DKE的优势之外，我们还提供了关于DKE如何继续发展和进步对该领域贡献的见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data & Knowledge Engineering 工程技术-计算机：人工智能

CiteScore

5.00

自引率

0.00%

发文量

审稿时长

6 months

期刊介绍： Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKE reaches a world-wide audience of researchers, designers, managers and users. The major aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of these systems.