Supplementary Materials for: MULTI-LAYERED OPEN DATA, DIFFERENTIAL PRIVACY, AND SECURE ENGINEERING: THE OPERATIONAL FRAMEWORK FOR ENVIRONMENTAL DIGITAL TWINS

Overview This repository contains the revised manuscript and supporting datasets for the research article titled "Multi-layered Open Data, Differential Privacy, and Secure Engineering: The Operational Framework for Environmental Digital Twins". Repository Contents 1. Revised Article (Draft): The full text of the manuscript, updated to address reviewer comments and incorporating final edits regarding the GDPR/NIS2 operational framework. 2. Supplementary Material S1 (PRISMA Protocol): Detailed search strategy, inclusion/exclusion criteria, and flow diagram for the systematic literature review (2018–2025), compliant with PRISMA 2020 standards. 3. Supplementary Material S2 (Validation): Protocols for Monte Carlo simulations, sensitivity analysis results, and convergence metrics used to validate the privacy-utility trade-offs. 4. Supplementary Material S3 (Mappings): Extended traceability matrices linking environmental data lifecycle stages to specific GDPR articles and NIS2 controls.Abstract. Sustainable urban development increasingly relies on hyperlocal environmental analytics created by smart city platforms that combine stationary and mobile sensors, Earth observations, meteorology, and land-use data. However, accurate spatio-temporal resolution can provide indirect identification and amplify cybersecurity threats. This article proposes the regulatory and technical mapping that implements the General Data Protection Regulation (GDPR) and the Network and Information Security Directive (NIS2) throughout the lifecycle of environmental data – reception, transport, storage, analytics, sharing and publication. The methods combine doctrinal legal analysis, a review of the scope of recent research, formalized compliance modelling, modelling g with synthetic city-scale datasets, expert identification, and demonstration of integrated analytics. The demonstration links deep evaluation of neural abnormalities (convolutional plus recurrent layers), short-term Fourier transform of sensor signals, byte-to-image telemetry fingerprints, and protocol event counters, thereby tracking detection to explanatory evidence and to control actions. Deliverables include: a matrix aligning lifecycle stages with GDPR principles and rights, as well as with the responsibilities of NIS2; a checklist for assessing the impact on data protection, which takes into account the risks of fairness and stigmatization; a basic set of controls for identification and access, secure design, monitoring, continuity, supplier assurance, and incident reporting; as well as a multi-layered publishing strategy that combines transparency with privacy through aggregation, delayed release, differentiated privacy budgets, and research enclaves. The visualization confirms that technical signals can be included in audit-ready reporting and automated response, while the guidelines legally clarify the relevant bases for common use cases such as air quality assurance networks, noise mapping, citizen sensor applications, and mobility and exposure modelling. The effects of the policy emphasize shared services for small municipalities, supply chain security, and ongoing review to counteract the mosaic effect. Overall, the study shows how cities can maximize environmental and social value based on environmental data, while maintaining privacy, sustainability, and equity by design.