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Supplementary Materials for "From Static Schedules to Consent-Driven Retention: An Approach to GDPR Storage Limitation Enforcement"

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Zenodo2026-06-30 更新2026-08-01 收录
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Supplementary materials for the paper "From Static Schedules toConsent-Driven Retention: An Approach to GDPR Storage LimitationEnforcement" submitted to the 19th International Workshop on DataPrivacy Management (DPM 2026), co-located with ESORICS 2026. This deposit contains: (i) the complete storage limitationmetamodel extension diagram showing five new classes(RetentionPolicy, RetentionState, ErasureTrigger, LegalHold,RetentionAuditRecord); (ii) a typed relationship catalogue specifying all 21 relationshipsin PDF grouped into four categories: core retention–purpose–consent linkage (7),erasure trigger linkage (5), legal hold linkage (4), and auditand constraint enforcement (5);(iii) a graphical model of the storage limitation extension appliedto the ZipFin UK open banking scenario in the DIAPROD modellingtool, containing base ConsentML constructs (actors, consents, legalbases, purposes, personal data) connected to extension constructs(three retention policies, two retention states, one erasuretrigger, one legal hold, one erasure candidate, and two auditrecords) through the 21 typed relationships; and (iv) amachine-readable JSON instance of the complete case study model(31 nodes, 66 edges, 16 node types, 29 edge types) exported fromthe DIAPROD tool in ConsentML-JSON format for programmaticvalidation and reproducibility. The artefacts support the doctoral research by demonstratingconsent-derived retention enforcement, purpose-linked erasure,legal hold suspension under Art. 17(3), multi-purpose retentionconflict resolution, and audit trail completeness grounded in GDPRArticles 5(1)(e), 17, and 25. The extension integrates withConsentML, a metamodel-based modelling language for dynamic consentwithin the DIAPROD (Dynamic Data Protection by Design) framework,described in: Daniels, S.O., Mouratidis, H.: ConsentML: AModelling Language for Dynamic Consent Modelling. In: RCIS 2026,LNBIP, vol. 585, pp. 542–557. Springer (2026).https://doi.org/10.1007/978-3-032-26836-5_33 All materials are provided in open formats for reproducibility.

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2026-06-30
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