Digital Product Passports (DPPs) are emerging as a core instrument of the European Union’s sustainability and circular economy agenda. Introduced under the Ecodesign for Sustainable Products Regulation (ESPR), DPPs aim to make structured, lifecycle-oriented product information digitally accessible to support ecodesign enforcement and circular value chains. Textiles are a priority product group due to fragmented supply chains, high environmental impacts, and low circularity. However, implementation remains uncertain in practice, particularly with respect to which information should be prioritised to ensure both regulatory alignment and feasibility across heterogeneous supply-chain actors.

This paper addresses this gap by proposing a prioritised information framework for textile DPP readiness. The study follows a two-stage approach: (i) extraction and consolidation of candidate information requirements from regulatory sources, standardisation outputs, and sector initiatives; and (ii) validation through interviews with textile companies to assess current maturity and identify priority information areas.

The results translate policy direction and industry input into a set of prioritised categories that can guide near-term implementation and remain extensible as delegated acts and harmonised standards evolve. The paper provides practical guidance on where to focus data collection and governance efforts first to support interoperable and scalable textile DPP implementation.

The maritime industry faces increasing regulatory pressure to reduce greenhouse gas emissions within a tight timeframe. At the same time, the large volumes of operational data continuously generated by vessels remain fragmented and underexploited for intelligent decision support. Effective mar itime decarbonisation requires platforms capable of ingesting and harmonising heterogeneous vessel data at scale, executing domain-specific AI and digital twin models in near real time, and delivering AI-enabled decision support and actionable guidance for vessel operations and lifecycle management to stakeholders with diverse technical backgrounds, within a trustworthy multi stakeholder data governance framework. Building on a previously developed platform, this paper presents an enhanced architecture designed to enable AI-driven decision support in maritime operations, introducing five principal architectural advances: a Delta Lake lakehouse replacing the legacy relational data ware house; Dagster-based AI workflow orchestration and MLflow model lifecycle management, superseding Airflow pipelines; a Digital Twin Ecosystem providing continuously updated vessel specific decision support applications; an agentic AI framework enabling goal-directed interaction via LangFlow and the Model Context Protocol; and a zero-trust security model enforcing Attribute-Based Access Control (ABAC) and cryptographic pro tection through Ciphertext-Policy Attribute-Based Encryption (CP-ABE). The paper describes the architectural evolution from the original platform, details each component of the enhanced design and the rationale behind key technology choices, and dis cusses the platform’s current deployment and validation status.

Mobility data spaces depend on logging to ensure accountability and regulatory compliance. However, major reference architectures only offer fragmentary guidance on this topic. Earlier International Data Space models centered on a clearing house. The Reference Architecture Model 5 replaces the former Clearing House concept with an observability approach, but leaves interoperable logging requirements unspecified. Gaia-X removed its data exchange logging service, and the Data Space Support Center only implicitly covers logging. As a result, implementations deploy heterogeneous, non-interoperable solutions. This paper emphasizes the necessity of explicit and sophisticated logging mechanisms in mobility data spaces. Drawing on representative use cases, such as safety-related traffic information, the Data for Road Safety ecosystem, the Euro-NCAP evaluation, Mobilithek operations, consent management, and event-driven smart-contract scenarios, we derive functional and technical logging requirements. Then, we propose a conceptual Logging House reference architecture that combines extended transaction logging, event-based logging, smart-contract evaluation, and cross-data-space traceability based on Self-Sovereign Identity. This architecture can serve as a generic blueprint for mobility and other sectoral or industrial data spaces.

Classic vehicles represent significant cultural artifacts whose historical and financial value depends critically on accurate, trustworthy documentation. However, existing approaches to vehicle history management suffer from fragmented records, susceptibility to tampering, and limited mechanisms for verified multi-stakeholder contributions. This paper presents \emph{ClassicsChain}, a blockchain-powered platform designed to address these challenges through a transparency-focused architecture for the preservation of classic vehicle history.

Building on prior work demonstrating blockchain's viability for securing vehicle history records, this research advances the development of a comprehensive ecosystem that transforms vehicle documentation from static, isolated records into dynamic, continuously enriched historical passports. The platform employs a hybrid architecture combining off-chain data storage with public blockchain anchoring, enabling cryptographic verification of all recorded information while preserving data privacy through role-based access control and configurable sharing mechanisms.

ClassicsChain implements a multi-stakeholder contribution model where vehicle owners and certified entities can each contribute verifiable historical data. The system generates Content Identifiers by deterministic hashing of canonically encoded data, which are anchored to a public blockchain to create immutable audit trails of vehicle histories. We describe the system architecture, implementation details, and discuss how this approach balances transparency with privacy requirements for sensitive vehicle records.