4.6 Review

A Systematic Literature Review on Enterprise Architecture Visualization Methodologies

期刊

IEEE ACCESS
卷 8, 期 -, 页码 96404-96427

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.2995850

关键词

Visualization; Computer architecture; Unified modeling language; Organizations; Systematics; Information systems; Enterprise architecture; business modeling; visualization methodology; systematic literature review

向作者/读者索取更多资源

EA (Enterprise Architecture) visualization methodologies have been explored by researchers and engineers to conduct EA modeling. The objectives of EA modeling are to clarify enterprise strategies, visualize business processes, and model information systems to manage resources, improve organization structure, adjust information strategy, and create new business value. Therefore, EA models can be broadly applied in various fields. For example, the applications include business modeling, information system architecture design, technology infrastructure configuration, software maintenance, and system security analysis. As the primary source of information, EA models are of paramount importance to researchers, architects, and developers. However, up to now, the purpose and means of these EA visualization methods have never been systematically analyzed and discussed, and a generalized EA visualization methodology with the ability to meet different demands is needed. The paper narrows this gap by conducting a systematic literature review on enterprise architecture visualization methodologies. In this study, 112 papers are retrieved by a manual search in 5 academic databases, a systematic literature review on EA visualization is explained to show a systematized category of visualization approaches, and then a general visualization approach is proposed by systematically reviewing the papers. Finally, the paper is concluded by discussing the contributions and limitations of the study.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据