{"ID":2836020,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.22513","arxiv_id":"2511.22513","title":"Declarative Policy Control for Data Spaces: A DSL-Based Approach for Manufacturing-X","abstract":"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.","short_abstract":"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, predictiv...","url_abs":"https://arxiv.org/abs/2511.22513","url_pdf":"https://arxiv.org/pdf/2511.22513v1","authors":"[\"Jérôme Pfeiffer\",\"Nicolai Maisch\",\"Sebastian Friedl\",\"Matthias Milan Strljic\",\"Armin Lechler\",\"Oliver Riedel\",\"Andreas Wortmann\"]","published":"2025-11-27T14:45:58Z","proceeding":"cs.SE","tasks":"[\"cs.SE\"]","methods":"[\"Generative Adversarial Network\"]","has_code":false}