159 research outputs found
Towards Interoperable Research Infrastructures for Environmental and Earth Sciences
This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a âreference model guidedâ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions
Towards Interoperable Research Infrastructures for Environmental and Earth Sciences
This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a âreference model guidedâ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions
Earth Observation Open Science and Innovation
geospatial analytics; social observatory; big earth data; open data; citizen science; open innovation; earth system science; crowdsourced geospatial data; citizen science; science in society; data scienc
Destination Earth: Survey on âDigital Twinsâ technologies and activities, in the Green Deal area
Digital Twins have been around for decades, especially in industrial processes. However, with the recent advent of transformative digital technologies (i.e. IoT, AI, ML, Big Data analytics, and ubiquitous connectivity) Digital Twins are changing most of the society sectors, providing the most advance pattern to make the physical and the digital worlds interact.
Naturally, this is also true for the scientific sector, and in particular those disciplines that are engaged in understanding and addressing the Global Change effects. Thanks to the Digital Twins growing development, for the first time, it is possible to envision a digital replica of important natural and social phenomena and processes, trying to anticipate their behaviour. There exist diverse definitions of Digital Twins, reflecting the diverse concerns of the industrial, scientific, and standardization sectors (in particular IEEE and ISO/IEC), which have been working on their description and realization.
The main interaction features characterizing a Digital Twin are:
- Interoperability;
- Information Model;
- Data Exchange;
- Administration;
- Synchronization;
- Push mode (Publish Subscribe).
According the scientific research, there is still the need to address the following challenges to push Digital Twins implementation and effective use:
- Unify data and model standards;
- Share data and models;
- Innovate on services;
- Establish forums.
In industry, Digital Twins are well used in âverticalâ sectors/application areas, including: manufacturing, energy, smart cities, farming, building, healthcare. For the applied scientific and research areas, this preliminary study recognized several areas.JRC.B.6-Digital Econom
Technologies and Applications for Big Data Value
This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part âTechnologies and Methodsâ contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part âProcesses and Applicationsâ details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems
Emerging approaches for data-driven innovation in Europe: Sandbox experiments on the governance of data and technology
Europeâs digital transformation of the economy and society is one of the priorities of the current Commission
and is framed by the European strategy for data. This strategy aims at creating a single market for data
through the establishment of a common European data space, based in turn on domain-specific data spaces
in strategic sectors such as environment, agriculture, industry, health and transportation. Acknowledging the
key role that emerging technologies and innovative approaches for data sharing and use can play to make
European data spaces a reality, this document presents a set of experiments that explore emerging
technologies and tools for data-driven innovation, and also deepen in the socio-technical factors and forces
that occur in data-driven innovation. Experimental results shed some light in terms of lessons learned and
practical recommendations towards the establishment of European data spaces
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