Science and Technology Parks (STPs) are increasingly expected to contribute to the transition towards a circular economy, not only by hosting innovative firms but also by enabling collaboration, experimentation, knowledge transfer and territorial innovation. This paper analyses how Spanish STPs are integrating circular economy approaches through different strategic and operational models within the framework of the European project 3D-CIRCULAR. The study adopts a qualitative multiple-case approach based on individual meetings with parks, a coordination session held at Transfiere, and a thematic webinar focused on circular economy strategies and good practices. The analysis identifies several complementary modes of contribution: parks acting as direct promoters of circular projects, facilitators of ecosystem collaboration, demonstration environments for applied innovation, hosts of circular frontrunner firms, and connectors between business, academia and training. The findings show that the role of STPs in circular economy is heterogeneous but strategically coherent. Their added value lies less in real-estate provision than in intermediation, validation, dissemination and scaling. The paper argues that Spanish STPs should be understood as circular economy enablers whose diverse practices offer transferable lessons for regional innovation policy and for European initiatives linking circularity, digitalisation and skills development.

AI-assisted microcredential pathways rely on career-related learner data to support competence profiling, recommendations, and certification; however, the legal status of these data is often underspecified in educational AI governance. Using the 3D-CIRCULAR project as an operational context, this paper undertakes a doctrinal legal analysis supplemented by normative governance design to examine whether and how such processing can comply with the GDPR. The analysis addresses four issues: contextual identifiability of career-related learner data, purpose limitation and data minimisation, lawful-basis selection and profiling safeguards, and allocation of controller and processor responsibility in a thirty-two-partner consortium. The paper argues that career-related inputs and AI-generated inferences should be treated as personal data when they relate to an identified or identifiable learner, especially in specialised cohorts and document-based workflows. On that basis, it proposes a competence-justified privacy-by-design framework that links each data element to a defined competence, pathway, or certification purpose and translates legal requirements into technical, organisational, and contractual controls. The contribution is therefore not an empirical validation study, but an operational governance model for lawful, proportionate, and accountable deployment of AI-assisted microcredential pathways.

Current scaling trajectories for Generative AI, typified by linear supply-side "stacks," prioritize performance density while externalizing significant thermodynamic and material costs. As the "Twin Transition" of green and digital transformation accelerates, the industry faces technology gaps—including Scope 3 emissions and e waste recycling—that impede sustainable scaling and lead to social tensions. This study proposes a Regenerative Socio Technical (RST) roadmap that repurposes the Sustainable Production and Consumption (SPaC) system map to reframe AI infrastructure as a system-of-systems governed ultimately by planetary limits. By integrating the IEEE IRDS™ roadmap regarding the environmental sustainability of semiconductor facilities, the study proposes a metabolic circuit framework that centers "Values and Needs" within SPaC loops. This study identifies critical gaps in current Nvidia-centric roadmaps and proposes a competing reference architecture. It demonstrates how a spontaneous order of resource parsimony and metabolic accountability can provide an actionable pathway for regulatory compliance and industrial resilience in the digital circular economy.

The transition to a circular economy in the furniture sector requires more than material substitution, improved recycling, or isolated eco-design measures. It also depends on digital tools that can transform fragmented product information into actionable knowledge for design, production, use, repair, refurbishment, recycling, and regulatory compliance. This paper presents CIR4FUN as a project-based contribution to the Digital Circular Economy in the European furniture sector. CIR4FUN develops and integrates a set of digital tools, including a Furniture Digital Product Passport (DPP), a Furniture Assessment System (FAS), secure data exchange mechanisms through a Furniture Data Space, eco-design and AI-supported methods, and digital support for circular business models. Core project results demonstrate how these tools address key barriers to circularity, including fragmented stakeholder data flows and the lack of actionable information for repair, reuse, and recycling. CIR4FUN enables lifecycle transparency, stakeholder collaboration, measurable circularity assessment, and integration of digital tools with value-retention business models. By conducting these tools in real supply chain contexts, the project generates new insights into data interoperability, usage rights, governance, and regulatory alignment. These findings position CIR4FUN as an innovative digital ecosystem that operationalises circular strategies across the furniture value chain and offers a replicable framework to advance the Digital Circular Economy in similar industrial sectors.