吉林大学学报(信息科学版) ›› 2025, Vol. 43 ›› Issue (6): 1323-1330.

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面向SBVR的业务表示模型向OWL2转换方法

袁 满, 夏安琦, 袁靖舒, 李洪欣   

  1. 东北石油大学 计算机与信息技术学院, 黑龙江 大庆 163318
  • 收稿日期:2024-10-22 出版日期:2025-12-08 发布日期:2025-12-08
  • 通讯作者: 袁靖舒(1992— ), 男, 吉林农安人, 东北石油大学讲师, 博士,硕士生导师, 主要从事知识组织、 知识图谱等研究, (Tel)86-18811139711(E-mail)yuanjingshu@ nepu. edu. cn。 E-mail:yuanjingshu@ nepu. edu. cn
  • 作者简介:袁满(1965— ), 男, 吉林农安人, 东北石油大学教授, 博士生导师, 主要从事数据科学、 知识组织理论与技术, (Tel)86-15765959186(E-mail)yuanman@ nepu. edu. cn
  • 基金资助:
    海南省哲学社会科学规划课题基金资助项目(HNSK(QN)24-53)

Conversion Method from SBVR Oriented Business Representation Model to OLW2

YUAN Man, XIA Anqi, YUAN Jingshu, LI Hongxin   

  1. School of Computer and Information Technology, Northeast Petroleum University, Daqing 163318, China
  • Received:2024-10-22 Online:2025-12-08 Published:2025-12-08

摘要:

针对现有业务规则建模标准 SBVR( Semantics of Business Vocabulary and Business Rules)主要面向业务专家, 无法被计算机系统直接理解的问题, 基于最新的 SBVR 2019 标准, 提出了一种 SBVR 向 Web 本体语言OWL2(Web Ontology Language)的转换方法。首先, 通过分析 SBVR 和 OWL2 的结构差异, 设计了相应的映射规则和转换算法; 其次, 开发了一个 SBVR 到 OWL2 的在线转换系统, 以标准化、可扩展的方式实现了业务流程的语义化; 最后, 通过石油领域的业务流程案例验证了该方法的可行性和实用性, 证明了其在促进企业数字化转型中的应用潜力, 并能为企业在业务流程的语义化和跨系统的知识共享方面提供有效的技术解决方案。

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Abstract:

In the digital transformation of enterprises, the standardization and semanticization of business processes are the key challenges. However, the current business rules modeling standard SBVR ( Semantics of Business Vocabulary and Business Rules ) is mainly targeted at business experts and can not be directly understood by computer systems. To address this issue, a method for converting SBVR into the OWL2 ( Web Ontology Language) based on the latest SBVR 2019 standard is proposed. First, the structural differences
between SBVR and OWL2 are analyzed, and corresponding mapping rules and conversion algorithms are designed. Second, an online SBVR-to-OWL2 conversion system is developed to achieve the semanticization of business processes in a standardized and extensible manner. Finally, the feasibility and practicality of the proposed method are validated through a case study in the petroleum industry's business processes, demonstrating its potential for promoting digital transformation in enterprises. This study provides an effective technical solution for the semanticization of business processes and knowledge sharing across systems.

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中图分类号: 

  • TP311. 13