Data Spaces

This open access book aims to educate data space designers to understand what is required to create a successful data space. It explores cutting-edge theory, technologies, methodologies, and best practices for data spaces for both industrial and personal data and provides the reader with a basis for understanding the design, deployment, and future directions of data spaces. The book captures the early lessons and experience in creating data spaces. It arranges these contributions into three parts covering design, deployment, and future directions respectively. The first part explores the design space of data spaces. The single chapters detail the organisational design for data spaces, data platforms, data governance federated learning, personal data sharing, data marketplaces, and hybrid artificial intelligence for data spaces. The second part describes the use of data spaces within real-world deployments. Its chapters are co-authored with industry experts and include case studies of data spaces in sectors including industry 4.0, food safety, FinTech, health care, and energy. The third and final part details future directions for data spaces, including challenges and opportunities for common European data spaces and privacy-preserving techniques for trustworthy data sharing. The book is of interest to two primary audiences: first, researchers interested in data management and data sharing, and second, practitioners and industry experts engaged in data-driven systems where the sharing and exchange of data within an ecosystem are critical

Data Spaces

This open access book aims to educate data space designers to understand what is required to create a successful data space. It explores cutting-edge theory, technologies, methodologies, and best practices for data spaces for both industrial and personal data and provides the reader with a basis for understanding the design, deployment, and future directions of data spaces. The book captures the early lessons and experience in creating data spaces. It arranges these contributions into three parts covering design, deployment, and future directions respectively. The first part explores the design space of data spaces. The single chapters detail the organisational design for data spaces, data platforms, data governance federated learning, personal data sharing, data marketplaces, and hybrid artificial intelligence for data spaces. The second part describes the use of data spaces within real-world deployments. Its chapters are co-authored with industry experts and include case studies of data spaces in sectors including industry 4.0, food safety, FinTech, health care, and energy. The third and final part details future directions for data spaces, including challenges and opportunities for common European data spaces and privacy-preserving techniques for trustworthy data sharing. The book is of interest to two primary audiences: first, researchers interested in data management and data sharing, and second, practitioners and industry experts engaged in data-driven systems where the sharing and exchange of data within an ecosystem are critical

Blockchain technology to secure data for digital twins throughout smart buildings’ life cycle in the context of the circular economy

Blockchain technology (BCT) can be leveraged for digital twins (DT) to enhance data security, collaboration, efficiency, and sustainability in the construction industry (CI) 4.0. This study aims to develop a novel technological framework and software architecture using BCT for DT throughout the lifecycle of smart building projects in the context of the circular economy (CE). The study identifies key challenges and technological factors affecting BCT adoption. It also identifies which project data types can benefit from BCT and the key factors and non-functional requirements (NFRs) necessary for the adoption of blockchain based digital twins (BCDT) in CI 4.0. The study finally proposes a software architecture and smart contract framework for BCDT decentralized applications (DApps) throughout the lifecycle of smart infrastructure projects. The study offers a technological framework – the decentralized digital twin cycle (DDTC) – with BCT to enhance trust, security, decentralization, efficiency, traceability, and transparency of information. The study found that the key data from the project lifecycle relevant for BCDTs relate to the BIM dimensions (3D, 4D, 5D, 6D, 7D, and 8D) and a novel contractual dimension (cD) is also proposed. Additionally, BCDT maturity Level 4 is proposed, leveraging BCT to enhance collaboration, process automation, and data sharing within a decentralized data value chain. The main NFRs for BCDTs are security, privacy, interoperability, data ownership, data integrity, and the decentralization and scalability of data storage. A five layered software architecture and a smart contracts framework using Non-Fungible Tokens (NFTs) are offered to address key industry use cases and their functional and non-functional requirements. The framework narrows the gaps identified around network governance, scalability, decentralization, interoperability, energy efficiency, computational requirements, and the integration of BCT with IoT, BIM, and DT. A cost analysis permitted developing criteria to evaluate the suitability of blockchain networks for BCDT applications in CI 4.0 based on key blockchain properties (security, decentralization, scalability, and interoperability). The study provides an industry-specific analysis and technological approach for BCDT adoption to address key challenges and improve sustainability for the CI 4.0. The findings provide key building blocks for industry practitioners to adopt and develop BCDT DApps further. The framework enables a paradigm shift towards decentralized ecosystems of united BCDTs where trust, collaboration, data sharing, information security, efficiency, and sustainability are improved throughout the lifecycle of smart infrastructure projects within a decentralized CE (DCE)

The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions

The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual reality (VR) technology. Many disciplines can benefit from the advancement of the Metaverse when accurately developed, including the fields of technology, gaming, education, art, and culture. Nevertheless, developing the Metaverse environment to its full potential is an ambiguous task that needs proper guidance and directions. Existing surveys on the Metaverse focus only on a specific aspect and discipline of the Metaverse and lack a holistic view of the entire process. To this end, a more holistic, multi-disciplinary, in-depth, and academic and industry-oriented review is required to provide a thorough study of the Metaverse development pipeline. To address these issues, we present in this survey a novel multi-layered pipeline ecosystem composed of (1) the Metaverse computing, networking, communications and hardware infrastructure, (2) environment digitization, and (3) user interactions. For every layer, we discuss the components that detail the steps of its development. Also, for each of these components, we examine the impact of a set of enabling technologies and empowering domains (e.g., Artificial Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on its advancement. In addition, we explain the importance of these technologies to support decentralization, interoperability, user experiences, interactions, and monetization. Our presented study highlights the existing challenges for each component, followed by research directions and potential solutions. To the best of our knowledge, this survey is the most comprehensive and allows users, scholars, and entrepreneurs to get an in-depth understanding of the Metaverse ecosystem to find their opportunities and potentials for contribution

The State of the Electronic Identity Market: Technologies, Infrastructure, Services and Policies

Authenticating onto systems, connecting to mobile networks and providing identity data to access services is common ground for most EU citizens, however what is disruptive is that digital technologies fundamentally alter and upset the ways identity is managed, by people, companies and governments. Technological progress in cryptography, identity systems design, smart card design and mobile phone authentication have been developed as a convenient and reliable answer to the need for authentication. Yet, these advances ar enot sufficient to satisfy the needs across people's many spheres of activity: work, leisure, health, social activities nor have they been used to enable cross-border service implementation in the Single Digital Market, or to ensure trust in cross border eCommerce. The study findings assert that the potentially great added value of eID technologies in enabling the Digital Economy has not yet been fulfilled, and fresh efforts are needed to build identification and authentication systems that people can live with, trust and use. The study finds that usability, minimum disclosure and portability, essential features of future systems, are at the margin of the market and cross-country, cross-sector eID systems for business and public service are only in their infancy. This report joins up the dots, and provides significant exploratory evidence of the potential of eID for the Single Digital Market. A clear understanding of this market is crucial for policy action on identification and authentication, eSignature and interoperability.JRC.DDG.J.4-Information Societ

Services State of Play - Compliance Testing and Interoperability Checking

The document contains an inventory of existing solutions for compliance testing and interoperability checking of services, the assumption being that the services are web services. Even if the emphasis is on geographical information and therefore on Geographical Information Systems, the document describes applicable solutions outside the geographical Information System domain.JRC.H.6-Spatial data infrastructure

Transportation interoperable planning in the context of food supply chain

L'alimentation est une nécessité de base de l'être humain, dont la survie dépend de la quantité et de la qualité de la nourriture ingérée. L'augmentation de la population requiert de plus en plus de nourriture, tandis que la qualité est associée aux contraintes des produits alimentaires comme une courte durée de vie ou la sensibilité à la température. L'augmentation de la demande entraîne une augmentation de la production alimentaire, répartie entre plusieurs sites de production appartenant à plusieurs entreprises de taille variée, qui peuvent utiliser les produits d'autres sites pour fabriquer leurs produits finaux. En outre, certains produits alimentaires doivent être transportés entre les sites et les produits finaux distribués à des détaillants et des consommateurs lointains en tenant compte des contraintes de produits alimentaires. Les activités exercées par ces entités incluent entre autres la production, la distribution, la vente, etc. et ces entités forment conjointement dans l'environnement de l'écosystème alimentaire une chaîne pour le traitement, l'emballage ou la livraison de nourriture. Ce réseau s'appelle une chaîne logistique alimentaire (FSC). En raison de leur nature distribuée, les FSC héritent des problèmes classiques des chaînes logistiques, mais doivent en plus gérer les problèmes découlant de la périssabilité des produits. Cette périssabilité rend extrêmement important le traitement d'enjeux tels que le maintien de la qualité, la prévision de la demande, la gestion des stocks (éviter les ruptures de stock ou les stocks excessifs), l’amélioration de l'efficacité du réapprovisionnement, de la production et du transport, la traçabilité et le suivi pour réagir aux perturbations. Il est donc nécessaire d'établir une collaboration entre les entités principales de l'écosystème alimentaire pour traiter tous ces enjeux. En outre, depuis l'arrivée des entreprises de transport spécialisées, un nouveau acteur a émergé appelé transporteur ou fournisseur de logistique. Ces transporteurs doivent collaborer avec les producteurs, les détaillants et même d'autres transporteurs afin de prendre en compte la demande future et les tendances, afin d'organiser leur réseau et les ressources, pour livrer des produits alimentaires en assurant sécurité et qualité. Ainsi, la collaboration est devenue vitale pour les FSC. La collaboration implique une bonne compréhension des informations échangées afin de minimiser les déplacements, le coût et la pollution environnementale. Des problèmes d'interopérabilité surgissent lorsque les partenaires impliqués utilisent des systèmes hétérogènes et différentes normes et terminologies. Les approches de collaborations existantes comme "Vendor Managed Inventory" (VMI) ou "Collaborative Planning Forecasting and Replenishment" (CPFR) ne prennent en compte que deux acteurs de la FSC : le producteur et le détaillant (acheteur et vendeur). En outre, elles ne considèrent pas la planification de la production et des transports comme des tâches de collaboration. En tenant compte des limitations ci-dessus, nous proposons, dans une première partie de cette thèse, une extension du modèle CPFR prennant en compte les aspects production et transport. Ce nouveau modèle C-PRIPT (Collaborative -Planning Replenishment Inventory Production and Transportation) inclut le transporteur et considère la planification de la production et des transports comme des activités de collaboration. Dans la deuxième partie, nous proposons un modèle distribué et interopérable I-POVES (Interoperable - Path Finder, Order, Vehicle, Environment and Supervisor) pour réaliser la planification des transports en collaboration avec les producteurs, les transporteurs et les détaillants, visant à une meilleure utilisation efficace des ressources de transport. Enfin, nous illustrons le fonctionnement du modèle I-POVES en l’appliquant sur un cas étude de chaîne logistique alimentaire. ABSTRACT : Eating is human’s basic necessity whose survival depends on both quantity and quality of food. Increasing population requires increasing in quantity of food, while quality is associated with the food product constraints like short shelf-life, temperature sensitiveness, climate etc. Increasing demand causes increase in food production, which is distributed between several production sites involving several distinct entities from small to large enterprises, where sites may use the intermediate products of other sites to produce the final products. Moreover, food products need to be transported between sites and final products to be distributed to faraway retailer sites and consumers considering the food product constraints. Activities performed by these entities include but not limited to: production, distribution, sales, etc. and these entities form jointly in the environment of food ecosystem a chain for food gathering, processing, packaging, delivery etc. This distributed network of enterprises is called food supply chain (FSC). Due to FSC’s distributed nature, it inherits not only the common problems also faced by other supply chain, but in addition has to deal with the problems arising from the perishability of food products. This perishability nature makes extremely important for FSC, the handling of issues such as maintaining the quality of food products, forecasting the product demand, managing the inventory according to the forecast to reduce out of stock or excessive inventory of products, improving the efficiency of replenishment, production and transportation, taking into account product future demand and tracing and tracking to react to disturbance. Finally, it is necessary to institute collaboration between the main entities of food ecosystem to deal with all of these issues. Furthermore, since the advent of specialized transport enterprises, a new actor has emerged called transporter or logistics provider in the FSC. These transporters have to collaborate with producers, retailers and even other transporters within FSC to take into account product future demands and trends to organise their transport network and resources to make possible the delivery of the food products with security, while maintaining the quality of the food products. Thus, collaboration became vital for FSC. Collaboration involves a good understanding of exchanged information in order to minimizing number of transport travels, cost and environmental pollution. Interoperability problem arises when each of the partners involved in FSC uses heterogeneous systems and uses different standards and terminologies for representing locations, product constraints, vehicles types etc. Furthermore, existing collaborative approaches like Quick Response, Efficient Consumer Response, Vendor Managed Inventory, Collaborative Planning Forecasting and Replenishment (CPFR), etc. take into account only two types of actors of FSC: buyer and seller (producer and retailer). Additionally, they don’t consider the production and transportation planning as collaborative tasks. Taking into account above limitations, we propose, in the first phase of this thesis, an extension of CPFR model, which take into account production and transportation aspects. This new model C-PRIPT (Collaborative -Planning Replenishment Inventory Production and Transportation) includes transporter actor and elaborates production and transportation planning as collaborative activities. In the second phase, we propose a distributed and interoperable transportation planning model I-POVES (Interoperable - Path Finder, Order, Vehicle, Environment and Supervisor) to realise collaborative transportation planning by collaborating producers, transporters and retailers, aiming at a better use of transport resources. Finally, we illustrate the functioning of I-POVES model by applying it on a case study of food supply chain

Designing Data Spaces

This open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is structured in four parts: Part I “Foundations and Contexts” provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II “Data Space Technologies” subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various “Use Cases and Data Ecosystems” from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several “Solutions and Applications”, eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more. Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty

Transportation interoperable planning in the context of food supply chain

Eating is human’s basic necessity whose survival depends on both quantity and quality of food. Increasing population requires increasing in quantity of food, while quality is associated with the food product constraints like short shelf-life, temperature sensitiveness, climate etc. Increasing demand causes increase in food production, which is distributed between several production sites involving several distinct entities from small to large enterprises, where sites may use the intermediate products of other sites to produce the final products. Moreover, food products need to be transported between sites and final products to be distributed to faraway retailer sites and consumers considering the food product constraints. Activities performed by these entities include but not limited to: production, distribution, sales, etc. and these entities form jointly in the environment of food ecosystem a chain for food gathering, processing, packaging, delivery etc. This distributed network of enterprises is called food supply chain (FSC). Due to FSC’s distributed nature, it inherits not only the common problems also faced by other supply chain, but in addition has to deal with the problems arising from the perishability of food products. This perishability nature makes extremely important for FSC, the handling of issues such as maintaining the quality of food products, forecasting the product demand, managing the inventory according to the forecast to reduce out of stock or excessive inventory of products, improving the efficiency of replenishment, production and transportation, taking into account product future demand and tracing and tracking to react to disturbance. Finally, it is necessary to institute collaboration between the main entities of food ecosystem to deal with all of these issues. Furthermore, since the advent of specialized transport enterprises, a new actor has emerged called transporter or logistics provider in the FSC. These transporters have to collaborate with producers, retailers and even other transporters within FSC to take into account product future demands and trends to organise their transport network and resources to make possible the delivery of the food products with security, while maintaining the quality of the food products. Thus, collaboration became vital for FSC. Collaboration involves a good understanding of exchanged information in order to minimizing number of transport travels, cost and environmental pollution. Interoperability problem arises when each of the partners involved in FSC uses heterogeneous systems and uses different standards and terminologies for representing locations, product constraints, vehicles types etc. Furthermore, existing collaborative approaches like Quick Response, Efficient Consumer Response, Vendor Managed Inventory, Collaborative Planning Forecasting and Replenishment (CPFR), etc. take into account only two types of actors of FSC: buyer and seller (producer and retailer). Additionally, they don’t consider the production and transportation planning as collaborative tasks. Taking into account above limitations, we propose, in the first phase of this thesis, an extension of CPFR model, which take into account production and transportation aspects. This new model C-PRIPT (Collaborative -Planning Replenishment Inventory Production and Transportation) includes transporter actor and elaborates production and transportation planning as collaborative activities. In the second phase, we propose a distributed and interoperable transportation planning model I-POVES (Interoperable - Path Finder, Order, Vehicle, Environment and Supervisor) to realise collaborative transportation planning by collaborating producers, transporters and retailers, aiming at a better use of transport resources. Finally, we illustrate the functioning of I-POVES model by applying it on a case study of food supply chain