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Article ; Online: Digital Ecosystems for Developing Digital Twins of the Earth

Stefano Nativi / Paolo Mazzetti / Max Craglia

Remote Sensing, Vol 13, Iss 2119, p

The Destination Earth Case

2021 Volume 2119

Abstract: 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 ... ...

Abstract	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.
Keywords	digital ecosystem ; digital twins ; green deal data space ; remote sensing ; earth observation ; system-of-systems engineering ; Science ; Q
Subject code	020
Language	English
Publishing date	2021-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Publishing NextGEOSS data on the GEOSS Platform

Roberto Roncella / Enrico Boldrini / Mattia Santoro / Paolo Mazzetti / João Andrade / Nuno Catarino / Stefano Nativi

Big Earth Data, Vol 7, Iss 2, Pp 413-

2023 Volume 427

Abstract: ABSTRACTThis paper is the second of a series that describes some of the main dataset resources presently shared through the GEOSS Platform. The GEOSS Platform was created as the technological tool to implement interoperability among the Global Earth ... ...

Abstract	ABSTRACTThis paper is the second of a series that describes some of the main dataset resources presently shared through the GEOSS Platform. The GEOSS Platform was created as the technological tool to implement interoperability among the Global Earth Observation System of Systems (GEOSS); it is a brokering infrastructure that presently brokers more than 190 autonomous data catalogs and information systems. This paper is focused on the analysis of the NextGEOSS datasets describing the data publishing process from NextGEOSS to the GEOSS platform. In particular, both the administrative registration and the technical registration were taken into consideration. One of the most important data shared by the GEOSS Platform are the NextGEOSS datasets: the present study provides some insights in terms of GEOSS user searches for NextGEOSS data.
Keywords	Earth observation ; GEOSS ; data interoperability ; data sharing ; data brokering services ; Geography. Anthropology. Recreation ; G ; Geology ; QE1-996.5
Subject code	020
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Taylor & Francis Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Publishing China satellite data on the GEOSS Platform

Roberto Roncella / Lianchong Zhang / Enrico Boldrini / Mattia Santoro / Paolo Mazzetti / Stefano Nativi

Big Earth Data, Vol 7, Iss 2, Pp 398-

2023 Volume 412

Abstract: ABSTRACTThis paper is the first of a series that describes some of the main dataset resources presently shared through the GEOSS Platform. The GEOSS Platform has been created to provide the technological tool to implement the Global Earth Observation ... ...

Abstract	ABSTRACTThis paper is the first of a series that describes some of the main dataset resources presently shared through the GEOSS Platform. The GEOSS Platform has been created to provide the technological tool to implement the Global Earth Observation System of Systems (GEOSS); it is a brokering infrastructure that presently brokers more than 190 autonomous data catalogs and information systems. The paper analyses the China Satellite datasets and describes the data publishing process from China GEOSS Data Provider to the GEOSS Platform considering both administrative registration as well as the technical registration. The China Satellite datasets are considered as one of the most important satellite data shared by the GEOSS Platform. The analysis provides some insights as well about GEOSS user searches for China Satellite datasets.
Keywords	GEOSS ; data interoperability ; data sharing ; satellite data ; Earth observation ; Geography. Anthropology. Recreation ; G ; Geology ; QE1-996.5
Subject code	020
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Taylor & Francis Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Publishing Eurac Research data on the GEOSS Platform

Roberto Roncella / Bartolomeo Ventura / Andrea Vianello / Enrico Boldrini / Mattia Santoro / Paolo Mazzetti / Stefano Nativi

Big Earth Data, Vol 7, Iss 2, Pp 428-

2023 Volume 450

Abstract: ABSTRACTThis paper is the third of a series that introduces some of the main dataset resources presently shared through the GEOSS Platform. The GEOSS Platform is a brokering infrastructure that brokers more than 190 autonomous information systems and ... ...

Abstract	ABSTRACTThis paper is the third of a series that introduces some of the main dataset resources presently shared through the GEOSS Platform. The GEOSS Platform is a brokering infrastructure that brokers more than 190 autonomous information systems and data catalogs; it was created to provide the technological tool to implement the Global Earth Observation System of Systems (GEOSS). This manuscript focuses on the analysis of Eurac Research datasets and illustrates the data publishing process to enroll the Eurac Research Data Provider to the GEOSS Platform through the administrative and technical registrations. The study provides an analysis of the GEOSS user searches for Eurac Research data in order to understand the main use of datasets of an important Data Provider.
Keywords	GEOSS ; data interoperability ; data sharing ; Eurac Research ; Earth observation ; Geography. Anthropology. Recreation ; G ; Geology ; QE1-996.5
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Taylor & Francis Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The VLab Framework

Mattia Santoro / Paolo Mazzetti / Stefano Nativi

Remote Sensing, Vol 12, Iss 1795, p

An Orchestrator Component to Support Data to Knowledge Transition

2020 Volume 1795

Abstract: 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 ... ...

Abstract	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.
Keywords	virtual earth laboratory ; orchestration ; data to knowledge ; environmental modeling ; interoperability ; geospatial technology ; Science ; Q
Subject code	690
Language	English
Publishing date	2020-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Paving the Way to Increased Interoperability of Earth Observations Data Cubes

Gregory Giuliani / Joan Masó / Paolo Mazzetti / Stefano Nativi / Alaitz Zabala

Data, Vol 4, Iss 3, p

2019 Volume 113

Abstract: Earth observations data cubes (EODCs) are a paradigm transforming the way users interact with large spatio-temporal Earth observation (EO) data. It enhances connections between data, applications and users facilitating management, access and use of ... ...

Abstract	Earth observations data cubes (EODCs) are a paradigm transforming the way users interact with large spatio-temporal Earth observation (EO) data. It enhances connections between data, applications and users facilitating management, access and use of analysis ready data (ARD). The ambition is allowing users to harness big EO data at a minimum cost and effort. This significant interest is illustrated by various implementations that exist. The novelty of the approach results in different innovative solutions and the lack of commonly agreed definition of EODC. Consequently, their interoperability has been recognized as a major challenge for the global change and Earth system science domains. The objective of this paper is preventing EODC from becoming silos of information; to present how interoperability can be enabled using widely-adopted geospatial standards; and to contribute to the debate of enhanced interoperability of EODC. We demonstrate how standards can be used, profiled and enriched to pave the way to increased interoperability of EODC and can help delivering and leveraging the power of EO data building, efficient discovery, access and processing services.
Keywords	Open Data Cube ; remote sensing ; geospatial standards ; landsat ; sentinel ; analysis ready data ; Bibliography. Library science. Information resources ; Z
Subject code	020
Language	English
Publishing date	2019-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A future for digital public goods for monitoring SDG indicators

Dong Liang / Huadong Guo / Stefano Nativi / Markku Kulmala / Zeeshan Shirazi / Fang Chen / Gretchen Kalonji / Dongmei Yan / Jianhui Li / Robert Duerler / Lei Luo / Qunli Han / Siming Deng / Yuanyuan Wang / Lingyi Kong / Thorsten Jelinek

Scientific Data, Vol 10, Iss 1, Pp 1-

2023 Volume 10

Abstract: Abstract 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 ... ...

Abstract	Abstract 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.
Keywords	Science ; Q
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Spatially enabling the Global Framework for Climate Services

Gregory Giuliani / Stefano Nativi / Andre Obregon / Martin Beniston / Anthony Lehmann

Climate Services, Vol 8, Iss C, Pp 44-

Reviewing geospatial solutions to efficiently share and integrate climate data & information

2017 Volume 58

Abstract: In November 2016, the Paris Agreement entered into force calling Parties to strengthen their cooperation for enhancing adaptation and narrowing the gap between climate science and policy. Moreover, climate change has been identified as a central ... ...

Abstract	In November 2016, the Paris Agreement entered into force calling Parties to strengthen their cooperation for enhancing adaptation and narrowing the gap between climate science and policy. Moreover, climate change has been identified as a central challenge for sustainable development by the United Nations 2030 Agenda for Sustainable Development. Data provide the basis for a reliable scientific understanding and knowledge as well as the foundation for services that are required to take informed decisions. In consequence, there is an increasing need for translating the massive amount of climate data and information that already exists into customized tools, products and services to monitor the range of climate change impacts and their evolution. It is crucial that these data and information should be made available not in the way that they are collected, but in the way that they are being used by the largest audience possible. Considering that climate data is part of the broader Earth observation and geospatial data domain, the aim of this paper is to review the state-of-the-art geospatial technologies that can support the delivery of efficient and effective climate services, and enhancing the value chain of climate data in support of the objectives of the Global Framework for Climate Services. The major benefit of spatially-enabling climate services is that it brings interoperability along the entire climate data value chain. It facilitates storing, visualizing, accessing, processing/analyzing, and integrating climate data and information and enables users to create value-added products and services.
Keywords	Climate services ; Essential Climate Variables ; Interoperability ; OGC standards ; GFCS ; GEO/GEOSS ; Meteorology. Climatology ; QC851-999 ; Social sciences (General) ; H1-99
Subject code	020
Language	English
Publishing date	2017-12-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Architecture of a Process Broker for Interoperable Geospatial Modeling on the Web

Lorenzo Bigagli / Mattia Santoro / Paolo Mazzetti / Stefano Nativi

ISPRS International Journal of Geo-Information, Vol 4, Iss 2, Pp 647-

2015 Volume 660

Abstract: 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 ... ...

Abstract	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.
Keywords	model web ; brokering ; processing services ; mediation ; service composition ; geographic information systems ; spatial data infrastructures ; Geography (General) ; G1-922
Subject code	020
Language	English
Publishing date	2015-04-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Knowledge generation using satellite earth observations to support sustainable development goals (SDG)

Gregory Giuliani / Paolo Mazzetti / Mattia Santoro / Stefano Nativi / Joost Van Bemmelen / Guido Colangeli / Anthony Lehmann

International Journal of Applied Earth Observations and Geoinformation, Vol 88, Iss , Pp 102068- (2020)

A use case on Land degradation

2020

Abstract: Land degradation is a critical issue globally requiring immediate actions for protecting biodiversity and associated services provided by ecosystems that are supporting human quality of life. The latest Intergovernmental Science-Policy Platform on ... ...

Abstract	Land degradation is a critical issue globally requiring immediate actions for protecting biodiversity and associated services provided by ecosystems that are supporting human quality of life. The latest Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services Landmark Assessment Report highlighted that human activities are considerably degrading land and threating the well-being of approximately 3.2 billion people.In order to reduce and ideally reverse this prevailing situation, national capacities should be strengthened to enable effective assessments and mapping of their degraded lands as recommended by the United Nations Sustainable Development Goals (SDGs). The indicator 15.3.1 (“proportion of land that is degraded over total land area”) requires regular data production by countries to inform and assess it through space and time. Earth Observations (EO) can play an important role both for generating the indicator in countries where it is missing, as well complementing or enhancing national official data sources.In response to this issue, this paper presents an innovative, scalable and flexible approach to monitor land degradation at various scales (e.g., national, regional, global) using various components of the Global Earth Observation System of Systems (GEOSS) platform to leverage EO resources for informing SDG 15.3.1. The proposed approach follows the Data-Information-Knowledge pattern using the Trends.Earth model (http://trends.earth) and various data sources to generate the indicator. It also implements additional components for model execution and orchestration, knowledge management, and visualization.The proposed approach has been successfully applied at global, regional and national scales and advances the vision of (1) establishing data analytics platforms that can potentially support countries to discover, access and use the necessary datasets to assess land degradation; and (2) developing new capacities to effectively and efficiently use EO-based resources.
Keywords	Land degradation ; Sustainable development goal ; Knowledge ; Earth observations ; VLab ; GEOSS ; Physical geography ; GB3-5030 ; Environmental sciences ; GE1-350
Subject code	333
Language	English
Publishing date	2020-06-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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