计算机科学
执行
数据治理
软件工程
访问控制
过程(计算)
数据共享
领域(数学分析)
计算机安全
资产(计算机安全)
数据交换
知识管理
数据科学
软件
过程管理
数据库
互操作性
工作流程
数据仓库
公司治理
建筑
软件体系结构
控制(管理)
数据存取
语义学(计算机科学)
数据建模
信息隐私
栏(排版)
语义网
协议(科学)
链接数据
万维网
作者
Jérôme Pfeiffer,Nicolai Maisch,Sebastian Friedl,Matthias Milan Strljic,Armin Lechler,Oliver Riedel,Andreas Wortmann
标识
DOI:10.48550/arxiv.2511.22513
摘要
The growing adoption of federated data spaces, such as in the GAIA-X and the International Data Spaces (IDS) initiative, promises secure and sovereign data sharing across organizational boundaries in Industry 4.0. In manufacturing ecosystems, this enables use cases, such as cross-factory process optimization, predictive maintenance, and supplier integration. Frameworks and standards, such as the Asset Administration Shell (AAS), Eclipse Dataspace Connector (EDC), ID-Link and Open Platform Communications Unified Architecture (OPC UA) provide a strong foundation to realize this ecosystem. However, a major open challenge is the practical description and enforcement of context-dependent data usage policies using these base technologies - especially by domain experts without software engineering backgrounds. Therefore, this article proposes a method for leveraging domain-specific languages (DSLs) to enable declarative, human-readable, and machine-executable policy definitions for sovereign data sharing via data space connectors. The DSL empowers domain experts to specify fine-grained data governance requirements - such as restricting access to data from specific production batches or enforcing automatic deletion after a defined retention period - without writing imperative code.
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