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Digital public goods (DPGs), if implemented with effective policies, can facilitate the realization of the United Nations Sustainable Development Goals (SDGs). However, there are ongoing deliberations on how to define DPGs and assure that society can extract the maximum benefit from the growing number of digital resources. The International Research Center of Big Data for Sustainable Development Goals (CBAS) sees DPGs as an important mechanism to facilitate information-driven policy and decision-making processes for the SDGs. This article presents the results of a CBAS survey of 51 respondents from around the world spanning multiple scientific fields, who shared their expert opinions on DPGs and their thoughts about challenges related to their practical implementation in supporting the SDGs. Based on the survey results, the paper presents core principles in a proposed strategy, including establishment of international standards, adherence to open science and open data principles, and scalability in monitoring SDG indicators. A community-driven strategy to develop DPGs is proposed to accelerate DPG production in service of the SDGs while adhering to the core principles identified in the survey. [ABSTRACT FROM AUTHOR]

The concept of Digital Earth (DE) was formalized by Al Gore in 1998. At that time the technologies needed for its implementation were in an embryonic stage and the concept was quite visionary. Since then digital technologies have progressed significantly and their speed and pervasiveness have generated and are still causing the digital transformation of our society. This creates new opportunities and challenges for the realization of DE. 'What is DE today?', 'What could DE be in the future?', and 'What is needed to make DE a reality?'. To answer these questions it is necessary to examine DE considering all the technological, scientific, social, and economic aspects, but also bearing in mind the principles that inspired its formulation. By understanding the lessons learned from the past, it becomes possible to identify the remaining scientific and technological challenges, and the actions needed to achieve the ultimate goal of a 'Digital Earth for all'. This article reviews the evolution of the DE vision and its multiple definitions, illustrates what has been achieved so far, explains the impact of digital transformation, illustrates the new vision, and concludes with possible future scenarios and recommended actions to facilitate full DE implementation. [ABSTRACT FROM AUTHOR]

The GEOSS Platform is a key contribution to the goal of building the Global Earth Observation System of Systems (GEOSS). It enables a harmonized discovery and access of Earth observation data, shared online by heterogeneous organizations worldwide. This work analyzes both what is made available in the GEOSS Platform by the data providers and how users are utilizing it including multiyear trends, updating a previous analysis published in 2017. The present statistics derive from a 2021 EOValue report funded by the European Commission. The offer of GEOSS Platform data has been the object of various analyses, including data provider characterization, data sharing trends, and data characterization (comprising metadata quality analysis, thematic analysis, responsible party identification, spatial–temporal coverage). GEOSS data demand has also been the object of several analyses, including data consumer characterization, utilization trends, and requested data characterization (comprising thematic analysis, spatial–temporal coverage, and popularity). Among the findings, a large amount of shared data, mostly from satellite sources, emerges with an issue of low metadata quality and related discovery match. Moreover, the trend in usage is decreasing. Therefore, the progressive disconnection of the GEOSS platform from its data Providers and Users and other possible causes are also reported. [ABSTRACT FROM AUTHOR]

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]

Global Change challenges are now systematically recognized and tackled in a growingly coordinated manner by intergovernmental organizations such as the United Nations. Heterogeneous observing networks provide the founded data sources to assess the Earth environmental status and take sound decisions to achieve a sustainable development. WMO Hydrological Observing System (WHOS) allows to discover and access historical and near real time hydrological observations. WHOS represents the hydrological contribution to the wider WIGOS-WIS system of WMO. It is a digital ecosystems framework contributed by a set of data providers and technical support centers. In this framework, three regional pilots were successfully completed. The WHOS architecture applies the services brokering style, implemented through the Discovery and Access Broker technology. A brokering approach makes a global system of systems possible and sustainable, where the different enterprise systems are enabled to interoperate, despite they implement heterogeneous communication interfaces and data models. In this manuscript, the WHOS brokering solution is detailed by recurring to the definition of a set of transversal viewpoints to describe the important aspects of the complex ecosystem –namely: enterprise, information, computational, engineering, and technological views. Finally, the three regional pilot ecosystems are described as successful cases of WHOS implementation. [ABSTRACT FROM AUTHOR]

The digital transformation of our society coupled with the increasing exploitation of natural resources makes sustainability challenges more complex and dynamic than ever before. These changes will unlikely stop or even decelerate in the near future. There is an urgent need for a new scientific approach and an advanced form of evidence-based decision-making towards the benefit of society, the economy, and the environment. To understand the impacts and interrelationships between humans as a society and natural Earth system processes, we propose a new engineering discipline, Big Earth Data science. This science is called to provide the methodologies and tools to generate knowledge from diverse, numerous, and complex data sources necessary to ensure a sustainable human society essential for the preservation of planet Earth. Big Earth Data science aims at utilizing data from Earth observation and social sensing and develop theories for understanding the mechanisms of how such a social-physical system operates and evolves. The manuscript introduces the universe of discourse characterizing this new science, its foundational paradigms and methodologies, and a possible technological framework to be implemented by applying an ecosystem approach. CASEarth and GEOSS are presented as examples of international implementation attempts. Conclusions discuss important challenges and collaboration opportunities. [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]

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]

In 2015, it was adopted the 2030 Agenda for Sustainable Development to end poverty, protect the planet and ensure that all people enjoy peace and prosperity. The year after, 17 Sustainable Development Goals (SDGs) officially came into force. In 2015, GEO (Group on Earth Observation) declared to support the implementation of SDGs. The GEO Global Earth Observation System of Systems (GEOSS) required a change of paradigm, moving from a data-centric approach to a more knowledge-driven one. To this end, the GEO System-of-Systems (SoS) framework may refer to the well-known Data-Information-Knowledge-Wisdom (DIKW) paradigm. In the context of an Earth Observation (EO) SoS, a set of main elements are recognized as connecting links for generating knowledge from EO and non-EO data – e.g. social and economic datasets. These elements are: Essential Variables (EVs), Indicators and Indexes, Goals and Targets. Their generation and use requires the development of a SoS KB whose management process has evolved the GEOSS Software Ecosystem into a GEOSS Social Ecosystem. This includes: collect, formalize, publish, access, use, and update knowledge. ConnectinGEO project analysed the knowledge necessary to recognize, formalize, access, and use EVs. The analysis recognized GEOSS gaps providing recommendations on supporting global decision-making within and across different domains. [ABSTRACT FROM AUTHOR]

This paper presents the Virtual Research Environment (VRE) enabling two European GEO Geohazard Supersites in Italy. According to GEO (Group on Earth Observation) vision, Geohazard Supersites provide access to spaceborne and in-situ geophysical data and models for selected sites prone to natural hazards -noticeably, earthquakes and volcano eruptions. The VRE was implemented in the framework of the Mediterranean Supersite Volcanoes (MED-SUV) project, funded by the European Commission. MED-SUV realized one of the European supersite demonstrators covering the two Permanent Supersites selected in Italy: Mt. Etna and Campi Flegrei/Vesuvius. The MED-SUV VRE provides advanced services for heterogeneous data and information management and sharing. MED-SUV started identifying the main supersite requirements including: the interoperability with existing data/information supply systems, the support of policy-based access control, the access to processing capabilities provided by external platforms, the management resources for publishing and sharing new products, the integration with significant global systems such as GEOSS and EPOS. MED-SUV adopted a System of Systems (SoS) approach to address interoperability with the identified heterogeneous systems supplying data and information. The SoS approach is based on a brokering architecture, where a specialized component (i.e the MED-SUV Broker: MSB) connects the existing and next-coming data sources leaving them autonomous. MSB carries out all the necessary mediation and harmonization tasks exposing standard interfaces enabling the interconnection with external systems like GEOSS and EPOS. In addition, MSB is accessible via a JavaScript library implementing Web APIs to facilitate the development of Web and mobile applications. [ABSTRACT FROM AUTHOR]

Data discoverability, accessibility, and integration are frequent barriers for scientists and a major obstacle for favorable results on environmental research. To tackle this issue, the Group on Earth Observations (GEO) is leading the development of the Global Earth Observation System of Systems (GEOSS), a voluntary effort that connects Earth Observation resources world-wide, acting as a gateway between producers and users of environmental data. GEO recognizes the importance of capacity building and education to reach large adoption, acceptance and commitment on data sharing principles to increase the capacity to access and use Earth Observations data. This article presents 'Bringing GEOSS services into practice' (BGSIP), an integrated set of teaching material and software to facilitate the publication and use of environmental data through standardized discovery, view, download, and processing services, further facilitating the registration of data into GEOSS. So far, 520 participants in 10 countries have been trained using this material, leading to numerous Spatial Data Infrastructure implementations and 1,000 tutorial downloads. This workshop lowers the entry barriers for both data providers and users, facilitates the development of technical skills, and empowers people. [ABSTRACT FROM AUTHOR]

This paper discusses the application of the Cross-Correlation Analysis (CCA) technique to multi-spatial resolution Earth Observation (EO) data for detecting and quantifying changes in forest ecosystems in two different protected areas, located in Southern Italy and Southern India. The input data for CCA investigation were elaborated from the forest layer extracted from an existing Land Cover/Land Use (LC/LU) map (time T1) and a more recent (T2, with T2 > T1) single date image. The latter consist of a High Resolution (HR) Landsat 8 OLI image and a Very High Resolution (VHR) Worldview-2 image, which were analysed separately. For the Italian site, the forest layer (1:5000) was first compared to the HR Landsat 8 OLI image and then to the VHR Worldview-2 image. For the Indian site, the forest layer (1:50,000) was compared to the Landsat 8 OLI image then the changes were interpreted using Worldview-2. The changes detected through CCA, at HR only, were compared against those detected by applying a traditional NDVI image differencing technique of two Landsat scenes at T1 and T2. The accuracy assessment, concerning the change maps of the multi-spatial resolution outputs, was based on stratified random sampling. The CCA technique allowed an increase in the value of the overall accuracy: from 52% to 68% for the Italian site and from 63% to 82% for the Indian site. In addition, a significant reduction of the error affecting the stratified changed area estimation for both sites was obtained. For the Italian site, the error reduction became significant at VHR (±2 ha) in respect to HR (±32 ha) even though both techniques had comparable overall accuracy (82%) and stratified changed area estimation. The findings obtained support the conclusions that CCA technique can be a useful tool to detect and quantify changes in forest areas due to both legal and illegal interventions, including relatively inaccessible sites (e.g., tropical forest) with costs remaining rather low. The data obtained through CCA intervention could not only support the commitments undertaken by the European Habitats Directive (92/43/EEC) and the Convention of Biological Diversity (CBD) but also satisfy UN Sustainable Development Goals (SDG). [ABSTRACT FROM AUTHOR]

This paper addresses the emerging issue of integrating data sharing and computing e-infrastructures for multidisciplinary applications. In the recent years several solutions have been proposed to implement digital infrastructures for sharing and processing scientific data and observations. Spatial data infrastructures currently enable effective and efficient geo-information data sharing in many disciplinary communities, and innovative solutions are under development to support new open data and linked data paradigms. In parallel, High Performance Computing systems, computing grids and more recently cloud services, enable fast processing of big data. However, the integration of data and computing e-infrastructures is a raising issue in multidisciplinary research. In the context of the Global Earth Observation System of Systems (GEOSS) initiative, an innovative approach has been proposed. Taking into account that the heterogeneity of data and computing e-infrastructures and related technologies cannot be reduced beyond a certain extent, since it is due to the need of supporting use cases and scenarios from different scientific communities, a brokering solution has been designed and developed. A Business Process Broker (BPB) is a component which takes a formal description of a scientific business process, and translates it in an executable process which can be run on multiple and remote processing and workflow services. In doing this it solves all the interoperability issues in a (semi-)automated way. It allows lowering the entry barrier for both computing service providers and users, decoupling the specification of the scientific process from the underlying enabling infrastructures. The paper presents and discusses a BPB use-case from the European project IASON, implementing an Earth Observation application involving satellite image mosaicking, HPC computing services and spatial data e-infrastructures. [ABSTRACT FROM AUTHOR]

The article discusses the implementation of the Chilean Architecture Implementation Pilot (AIP) project, within the Global Earth Observation System of Systems (GEOSS), for disaster prevention in Chile. Topics include the project was developed by the Chile Capacity Building Working Group, it was designed to reduce the vulnerability of the country to the disasters, and integration of data and metadata.

The identification of appropriate mechanisms for process sharing and reuse by means of composition is considered a key enabler for the effective uptake of a global Earth Observation infrastructure, currently pursued by the international geospatial research community. Modelers in need of running complex workflows may benefit from outsourcing process composition to a dedicated external service, according to the brokering approach. This work introduces our architecture of a process broker, as a distributed information system for creating, validating, editing, storing, publishing and executing geospatial-modeling workflows. The broker provides a service framework for adaptation, reuse and complementation of existing processing resources (including models and geospatial services in general) in the form of interoperable, executable workflows. The described solution has been experimentally applied in several use scenarios in the context of EU-funded projects and the Global Earth Observation System of Systems. [ABSTRACT FROM AUTHOR]

Global sustainability research requires an integrative research effort underpinned by digital infrastructures (systems) able to harness data and heterogeneous information across disciplines. Digital data and information sharing across systems and applications is achieved by implementing interoperability: a property of a product or system to work with other products or systems, present or future. There are at least three main interoperability challenges a digital infrastructure must address: technological, semantic, and organizational. In recent years, important international programs and initiatives are focusing on such an ambitious objective. This manuscript presents and combines the studies and the experiences carried out by three relevant projects, focusing on the heavy metal domain: Global Mercury Observation System, Global Earth Observation System of Systems (GEOSS), and INSPIRE. This research work recognized a valuable interoperability service bus (i.e., a set of standards models, interfaces, and good practices) proposed to characterize the integrative research cyber-infrastructure of the heavy metal research community. In the paper, the GEOSS common infrastructure is discussed implementing a multidisciplinary and participatory research infrastructure, introducing a possible roadmap for the heavy metal pollution research community to join GEOSS as a new Group on Earth Observation community of practice and develop a research infrastructure for carrying out integrative research in its specific domain. [ABSTRACT FROM AUTHOR]

This paper explores key issues in the development of open access to research data. The use of digital means for developing, storing and manipulating data is creating a focus on ‘data-driven science’. One aspect of this focus is the development of ‘open access’ to research data. Open access to research data refers to the way in which various types of data are openly available to public and private stakeholders, user communities and citizens. Open access to research data, however, involves more than simply providing easier and wider access to data for potential user groups. The development of open access requires attention to the ways data are considered in different areas of research. We identify how open access is being unevenly developed across the research environment and the consequences this has in terms of generating data gaps. Data gaps refer to the way data becomes detached from published conclusions. To address these issues, we examine four main areas in developing open access to research data: stakeholder roles and values; technological requirements for managing and sharing data; legal and ethical regulations and procedures; institutional roles and policy frameworks. We conclude that problems of variability and consistency across the open access ecosystem need to be addressed within and between these areas to ensure that risks surrounding a data gap are managed in open access. [ABSTRACT FROM AUTHOR]

For disciplinary and domain applications, systems interoperability largely deals with the adoption of agreed technologies, standards, specifications and interfaces with a disciplinary/domain service bus or means of information exchange, if available. However, multi-disciplinary efforts make more complex demands on the type of systems and arrangements needed to support cross-domain activities. Thus, interoperability among diverse disciplinary and domain systems must be pursued adopting more flexible and sustainable approaches. This paper discusses the challenges for multi-disciplinary interoperability. The recent Brokering approach is introduced; this solution aims at interconnecting the heterogeneous disciplinary and domain service buses, avoiding the imposition of any federated or common specification. It can deliver a range of services such as discovery and access through a Broker Framework. The Brokering approach has been successfully introduced by the EuroGEOSS research project and recently adopted by the GEOSS Common Infrastructure (GCI). US NSF EarthCube initiative also has recognized the importance of brokering for its reference architecture. The GI-* technology, empowering the EuroGEOSS and the GCI brokering frameworks, is presented and discussed. [ABSTRACT FROM PUBLISHER]

The implementation of the INSPIRE Directive in Europe and similar efforts around the globe to develop spatial data infrastructures and global systems of systems have been largely focusing on the adoption of agreed technologies, standards, and specifications to address the interoperability challenge. However, addressing the key scientific challenges of humanity in the 21st century requires a more comprehensive integrative research effort, which in turn may pose more complex requirements on the systems to be integrated, and increase the number of arrangements required to support them. This paper analyses the main challenges related to integrative interoperability, such as mutual understanding of requirements and methods, theoretical underpinning, and tacit knowledge. To illustrate our contribution to the integrative research, the paper proposes the flexible approach to interoperability, based on mediation and brokering, that has been implemented by the EuroGEOSS research project. It also demonstrates that this approach allows scientific and non-scientific stakeholders to overcome the increased complexity of the integration effort mentioned above and charts the trajectory for the evolution of current spatial data infrastructures. [ABSTRACT FROM PUBLISHER]

The Earth and Space Sciences Informatics division of European Geosciences Union (EGU) and the Open Geospatial Consortium jointly organised a special event entitled: 'Implementation of international geospatial standards for earth and space sciences event' - at the EGU General Assembly meeting held in Vienna, April 2009. The event objectives included: (a) to discuss the integration of information systems from different geosciences disciplines; (b) to promote and discuss the present process to scale from specific and monolithic systems towards independent and modular enabling infrastructures - forming an earth system science (ESS) infrastructure; and (c) to show some of the latest advances in implementing open standards. This manuscript introduces the event motivations and describes the abstract and holistic framework, which can be used to situate the topics and the developments presented by the event speakers. This manuscript introduces important, and relatively new technologies to build a multi-disciplinary geosciences information system: the System of Systems approach and the Model Driven Approach. To achieve that, three important information infrastructure categories are recognised: (a) ESS information infrastructure; (b) geospatial information infrastructure; and (c) distributed information infrastructure. Digital Earth should support the discussed framework to accelerate information transfer from theoretical discussions to applications, in all fields related to global climate change, natural disaster prevention and response, new energy-source development, agricultural and food security, and urban planning and management. [ABSTRACT FROM AUTHOR]

During the full cycle of the emergency management, Civil Protection operative procedures involve many actors belonging to several institutions playing different roles. In this context the sharing of information is a vital requirement to make correct and effective decisions. Therefore a European-wide technological infrastructure providing a distributed and coordinated access to different kinds of resources (data, information, services, expertise, etc.) could enhance existing Civil Protection applications and even enable new ones. In the recent years Grid technologies have reached a mature state providing a platform for secure and coordinated resource sharing between the participants in the so-called Virtual Organizations. Moreover the Earth and Space Sciences Informatics provide the conceptual tools for modelling the geospatial information shared in Civil Protection applications during its entire life cycle. Therefore a European Civil Protection e-infrastructure could be based on a Grid platform enhanced with Earth Sciences specific services. However Civil Protection applications stress the requirements of Earth Sciences research applications, for example in terms of real-time support. Therefore a set of high-level services specifically tailored for such applications must be built on top of the Grid platform. As a result of a requirement analysis, the FP6 project CYCLOPS has proposed an architectural framework for the future European Civil Protection e-Infrastructure. In this architecture a layer of high-level services tailored to Civil Protection applications is built on top of the EGEE Grid middleware. This architectural approach has been tested implementing a prototype of a grid-enabled RISICO, the application for wild fire risk assessment used by the Italian Civil Protection. [ABSTRACT FROM AUTHOR]

There is an ever-increasing need to integrate knowledge from the diverse disciplines engaged in studying the constituent parts of the complex Earth system. With the emergence of the Global Earth Observation System of Systems (GEOSS), which is bringing together thousands of previously isolated Earth observing systems, the necessity of establishing methods that will help in the integration of varied discipline information systems becomes even more urgent. The Group on Earth Observations (GEO) was established to oversee the creation of GEOSS which seeks to advance the convergence of Earth observing systems based on interoperability arrangements agreed to by consensus. We describe the specific approaches that GEO has proposed for achieving interoperability among its component systems and give an overview of the GEOSS Interoperability Process Pilot Project (IP3). The IP3 is helping to develop an advanced information infrastructure that supports the formation and operation of Earth System Science communities based on cross-disciplinary information exchange. This means moving from discipline-specific monolithic data-centric systems toward modular service-oriented information systems. GEOSS seeks to provide scientists, researchers, and decision makers with a persistent set of independent but interoperable information services that can be applied to address many pressing societal issues. The IP3 is furthering this cause by piloting a framework for multidisciplinary knowledge integration. [ABSTRACT FROM AUTHOR]

Access to real-time distributed Earth and Space Science (ESS) information is essential for enabling critical Decision Support Systems (DSS). Thus, data model interoperability between the ESS and DSS communities is a decisive achievement for enabling cyber-infrastructure which aims to serve important societal benefit areas. The ESS community is characterized by a certain heterogeneity, as far as data models are concerned. Recent spatial data infrastructures implement international standards for the data model in order to achieve interoperability and extensibility. This paper presents well-accepted ESS data models, introducing a unified data model called the Common Data Model (CDM). CDM mapping into the corresponding elements of the international standard coverage data model of ISO 19123 is presented and discussed at the abstract level. The mapping of CDM scientific data types to the ISO coverage model is a first step toward interoperability of data systems. This mapping will provide the abstract framework that can be used to unify subsequent efforts to define appropriate conventions along with explicit agreed-upon encoding forms for each data type. As a valuable case in point, the content mapping rules for CDM grid data are discussed addressing a significant example. [ABSTRACT FROM AUTHOR]

Part I. Presents a study which described an operational non-linear physical inversion (PIn) algorithm for precipitable and cloud liquid water estimate. Standard atmospheric temperature profile of the forward model; Validation of the forward model; Parameters retrieval for a fixed tropopause temperature.

Part II. Presents a study which estimated an integrated precipitable water vapor along with liquid water path and water vapor effective profile. Assessment of an operative procedure based on a non-linear physical inversion algorithm; Use of the Special Sensor Microwave/Imager and Tropical Rainfall Measuring Mission Microwave Imager radiometers in estimation; Statistical analysis and conclusions.

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]

The 21 papers in this special issue focus on interoperability architectures and arrangements for multi-disciplinary earth observation systems and applications. [ABSTRACT FROM PUBLISHER]

Over the last decades, to better proceed towards global and local policy goals, there was an increasing demand for the scientific community to support decision-makers with the best available knowledge. Scientific modeling is key to enable the transition from data to knowledge, often requiring to process big datasets through complex physical or empirical (learning-based AI) models. Although cloud technologies provide valuable solutions for addressing several of the Big Earth Data challenges, model sharing is still a complex task. The usual approach of sharing models as services requires maintaining a scalable infrastructure which is often a very high barrier for potential model providers. This paper describes the Virtual Earth Laboratory (VLab), a software framework orchestrating data and model access to implement scientific processes for knowledge generation. The VLab lowers the entry barriers for both developers and users. It adopts mature containerization technologies to access models as source code and to rebuild the required software environment to run them on any supported cloud. This makes VLab fitting in the multi-cloud landscape, which is going to characterize the Big Earth Data analytics domain in the next years. The VLab functionalities are accessible through APIs, enabling developers to create new applications tailored to end-users. [ABSTRACT FROM AUTHOR]