Abstract
Since supply chains have become complex and tracking a product's journey, from raw materials to the end of it's life has become more difficult. Consumers are demanding greater transparency about the materials origins and environmental impact of the products they buy. These new requirements, togeher with European Commission Green Deal strategy, lead to the concept of digital product passport (DPP). DPP could be seen as an instrument to boost circularity, however the DPP architecture and governance model still undefined and unclear. Data Governance in the context of the DPP acts as the backbone for ensuring accurate and reliable data within these passports or data models, leading to flawless traceability. This article approaches the DPPs and it's governance challenges, explaining how they function as digital repositories for a product's life cycle information and the concept of Data Governance. By understanding how these two concepts work together, we will explore a short use case within the footwear industry to show how DPP governance architecture might work in a distributed environment.

Abstract
This paper discusses the Digital Product Passport (DPP) as a key tool for achieving a circular economy. An architecture of the DPP is presented built upon the principles of data spaces and W3C Decentralized Identifiers (DIDs). By leveraging data spaces, the DPP enables secure and controlled data exchange among stakeholders, fostering transparency, traceability, and collaboration throughout the product's lifecycle. The use of decentralized identifiers ensures the uniqueness and verifiability of product-related information, facilitating seamless access and sharing of data. The DPP architecture offers a promising framework for realizing the circular economy by promoting resource efficiency, sustainable practices, and informed decision-making. © 2024 The Author(s). Published by Elsevier B.V.

Abstract
Considering the great challenge of implementing digital tools to improve collaboration in the value chain and promote the adoption of circularity strategies, as is the case with digital traceability tools and digital product passports. This paper presents an innovative proposal for implementing an industrial data sharing ecosystem, namely an architecture and platform for digital traceability between entities based on Data Spaces. To validate our proposal, a use case scenario was implemented as part of the BioShoes4All project.

Abstract
Gamification is a topic which aims to apply game elements to real world tasks, that results in a pleasant influence over a user behaviour towards an objective. Learning is one of the fields where gamification has been implemented and experimented to motivate students and improve their learning process. The first iterations account for the use of game elements such as points, levels and badges or achievements based on task completion according to rules set before. The learning tasks in this approach are not necessarily changed or take advantage of new forms of interactions and guidance. In this article we introduce the application of virtual reality, augmented reality, and machine learning as tools to improve upon the standard application of gamification, making the experience more immersive to the user. We hope to advance gamification to account for more elements, such as digital twins and digital aids in a learning application. In this article we detail possible scenarios for the application of virtual reality and augmented reality combined with machine learning in serious games and learning scenarios.

Abstract
The increased competitiveness in the industry sector and the pressure for companies to be more flexible to answer to the market changes, booted the investments in technologies with the aim at increasing the flexibility, productivity, and profit. To this paradigmatic change it is called digital transformation. In this context, companies try to find new way to deal with an old problem: The product production planning. Nowadays, production planning is a collaborative process that should address all supply chain network; thus, it is critical, complicated and a time-consuming process. This article focuses on the product production planning in the context of the footwear industry from a collaborative perspective, applying suppliers' assessment methods and forecasting models to optimize the production planning process, allowing companies to satisfy delivery dates. The results showed the importance of production planning in collaborative settings, but the adoption of machine learning methods reveal the need for data restructuring at the ERP and MRP levels.