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In modern society, citizens aspire to get trusted and reliable digital services to authenticate theirs to payments. With the COVID-19 crisis, online shopping’s fast growth has led citizens to increase registration in different systems. The registration is typically done without any guarantee that the involved business entity is trusted and that private data is managed adequately, namely according to the General Data Protection Regulation (GDPR). There are cases where online business adopts a federated authentication mechanism based on the existing and extensively adopted service providers, e.g., Facebook, and Google. With the European authorities’ complacency, this de facto trend seems to contribute to a dangerous unregulated digital services model. While avoiding the centralization risks, a possible alternative is to pursue the concept of regulated and competing digital online shops or services offered under a single collaborative model across Europe. Citizens aspire to get simple mechanisms based on a single provider for authentication and pay anywhere, even with some associated costs. In this direction, we propose a model that considers regulated providers managing citizens’ access to any online business in Europe, avoiding, in this way, the spreading of personal data across (business) organizations, thus decreasing the risk of personal data leaks. A collaborative network is foreseen to logically tie committed regulating authorities, providers, and digital online service providers. The proposed approach is ground on our previous research on systems integration, collaborative network infrastructure, and unified mobility payment services. This position paper offers a digital strategy for citizens, designated by Digital Person Ecosystem (DPE), which relies on Collaborative Networks concepts and centered on public authority leadership.

To perform data-centric research in environmental and earth sciences, re-searchers need effectively query, select and access data products from different research infrastructures. When providing observation data continuously, infrastructure is expected to create and deliver customised data products, e.g. for specific geo-regions, time durations or observation parameters, to enhance its ability to serve the research communities. Such kind of services often have time-critical requirements; some tasks need to be carried out within specific time windows when the data products are needed for re-al-time modelling or simulation frameworks.

The increasing volumes of data being produced, curated and made available by research infrastructures in the environmental science domain require services able to optimise the delivery staging and process of data on behalf of researchers. Specialised data services for managing the data lifecycle, for creating and delivering data products, and for customised data processing and analysis, all play a crucial role in how these research infrastructures serve their communities, and many of these activities are time-critical need-ing to be carried out frequently within specific time windows. We describe our experiences identifying the time-critical requirements of environmental scientists making use of computational research support environments. We also present a microservice based infrastructure optimisation suite, the Dynamic Real-time Infrastructure Planner, used for constructing virtual infra-structures for research applications on demand. This chapter is partially based on a recent paper presented in [1].

Effectively managing decentralized applications in cloud environments using a decentralized control paradigm is essential, as current cloud providers usually only offer a control interface for monitoring cloud infrastructures. This study proposes a decentralized service control framework for implementing the control across various organizations and coordinating collaboration among operators in a decentralized application. The proposed framework allows a consortium of organizations to control a shared distributed cloud infrastructure decentralized reliably. A consensus mechanism within the framework enables mutual coordination between the operators. This mechanism also uses an incentive protocol to enforce pro-active behavior and collaboration. We implement the framework with Hyperledger Fabric, and our experiments demonstrate its usability, reliability, and acceptable performance.