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Humankind is facing unprecedented global environmental and social challenges in terms of food, water and energy security, resilience to natural hazards, etc. To address these challenges, international organizations have defined a list of policy actions to be achieved in a relatively short and medium-term timespan. The development and use of knowledge platforms is key in helping the decision-making process to take significant decisions (providing the best available knowledge) and avoid potentially negative impacts on society and the environment. Such knowledge platforms must build on the recent and next coming digital technologies that have transformed society – including the science and engineering sectors. Big Earth Data (BED) science aims to provide the methodologies and instruments to generate knowledge from numerous, complex, and diverse data sources. BED science requires the development of Geoscience Digital Ecosystems (GEDs), which bank on the combined use of fundamental technology units (i.e. big data, learning-driven artificial intelligence, and network-based computing platform) to enable the development of more detailed knowledge to observe and test planet Earth as a whole. This manuscript contributes to the BED science research domain, by presenting the Virtual Earth Cloud: a multi-cloud framework to support GDE implementation and generate knowledge on environmental and social sustainability. [ABSTRACT FROM AUTHOR]

A long-term goal of environmental science and Earth observation is to enable the creation of a "Model Web" of semantically interconnected data and models. Geospatial models are usually exposed on the Web as services accessible through heterogeneous interfaces. However, such services, which represent instances of the paradigm called Model-as-a-Service (MaaS), cannot be easily exploited beyond their original use as defined by the service provider. To overcome this important limitation and better support transparency, reproducibility, replicability and reusability of the model (following the Open Science paradigm), we investigated the adoption of a Model-as-a-Resource (MaaR) approach, in which a model is considered a generic digital resource that, as such, can play different roles in different potential use cases. The proposed MaaR framework can play an important enabling role in the realization of those digital ecosystems that generate environmental knowledge. The main challenges and opportunities are discussed in the manuscript. • The Open Science/Knowledge paradigms require reusability of computational models. • Sharing models as runnable services is not sufficient for transparency/reusability. • A MaaR (Model-as-a-Resource) framework allows sharing models as full Web resources. • In a MaaR framework models can be reused beyond the intention of providers. • A MaaR framework requires a multi-style architecture (REST + SOA). [ABSTRACT FROM AUTHOR]

When defining indicators on the environment, the use of existing initiatives should be a priority rather than redefining indicators each time. From an Information, Communication and Technology perspective, data interoperability and standardization are critical to improve data access and exchange as promoted by the Group on Earth Observations. GEOEssential is following an end-user driven approach by defining Essential Variables (EVs), as an intermediate value between environmental policy indicators and their appropriate data sources. From international to local scales, environmental policies and indicators are increasingly percolating down from the global to the local agendas. The scientific business processes for the generation of EVs and related indicators can be formalized in workflows specifying the necessary logical steps. To this aim, GEOEssential is developing a Virtual Laboratory the main objective of which is to instantiate conceptual workflows, which are stored in a dedicated knowledge base, generating executable workflows. To interpret and present the relevant outputs/results carried out by the different thematic workflows considered in GEOEssential (i.e. biodiversity, ecosystems, extractives, night light, and food-water-energy nexus), a Dashboard is built as a visual front-end. This is a valuable instrument to track progresses towards environmental policies. [ABSTRACT FROM AUTHOR]

Measuring the achievement of a sustainable development requires the integration of various data sets and disciplines describing bio-physical and socio-economic conditions. These data allow characterizing any location on Earth, assessing the status of the environment at various scales (e.g. national, regional, global), understanding interactions between different systems (e.g. atmosphere, hydrosphere, biosphere, geosphere), and modeling future changes. The Group on Earth Observations (GEO) was established in 2005 in response to the need for coordinated, comprehensive, and sustained observations related to the state of the Earth. GEO's global engagement priorities include supporting the UN 2030 Agenda for Sustainable Development, the Paris Agreement on Climate, and the Sendai Framework for Disaster Risk Reduction. A proposition is made for generalizing and integrating the concept of EVs across the Societal Benefit Areas of GEO and across the border between Socio-Economic and Earth systems EVs. The contributions of the European Union projects ConnectinGEO and GEOEssential in the evaluation of existing EV classes are introduced. Finally, the main aim of the 10 papers of the special issue is shortly presented and mapped according to the proposed typology of SBA-related EV classes. [ABSTRACT FROM AUTHOR]

This manuscript discusses the key characteristics of the Digital Ecosystems (DEs) model, which, we argue, is particularly appropriate for connecting and orchestrating the many heterogeneous and autonomous online systems, infrastructures, and platforms that constitute the bedrock of a digitally transformed society. Big Data and AI systems have enabled the implementation of the Digital Twin paradigm (introduced first in the manufacturing sector) in all the sectors of society. DEs promise to be a flexible and operative framework that allow the development of local, national, and international Digital Twins. In particular, the "Digital Twins of the Earth" may generate the actionable intelligence that is necessary to address global change challenges, facilitate the European Green transition, and contribute to realizing the UN Sustainable Development Goals (SDG) agenda. The case of the Destination Earth initiative and system is discussed in the manuscript as an example to address the broader DE concepts. In respect to the more traditional data and information infrastructural philosophy, DE solutions present important advantages as to flexibility and viability. However, designing and implementing an effective collaborative DE is far more difficult than a traditional digital system. DEs require the definition and the governance of a metasystemic level, which is not necessary for a traditional information system. The manuscript discusses the principles, patterns, and architectural viewpoints characterizing a thriving DE supporting the generation and operation of "Digital Twins of the Earth". The conclusions present a set of conditions, best practices, and base capabilities for building a knowledge framework, which makes use of the Digital Twin paradigm and the DE approach to support decision makers with the SDG agenda implementation. [ABSTRACT FROM AUTHOR]