Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/150246
Título: A Framework for Big Data Sovereignty
Autor: Mertens, Christoph
Alonso, Jesús
Lázaro, Oscar
Palansuriya, Charaka
Böge, Gernot
Nizamis, Alexandros
Rousopoulou, Vaia
Ioannidis, Dimosthenis
Tzovaras, Dimitrios
Touma, Rizkallah
Tarzán, Miquel
Mallada, Diego
Figueiras, Paulo
Costa, Ruben
Graça, Diogo
Garcia, Gisela
Laibarra, Begoña
Celaya, Aitor
Sobonski, Piotr
Naeem, Azzam
Mozo, Alberto
Vakaruk, Stanislav
Sierra-García, J. Enrique
Pastor, Antonio
Rodríguez, Juan
Hildebrand, Marlène
Luniewski, Tomasz
Zietak, Wojciech
Lange, Christoph
Sipsas, Konstantinos
Poulakidas, Athanasios
Palavras-chave: Data Space
Data treasures
Data sharing
Trust
Digital sovereignty
EIDS
IDSA
Open source
Interoperability
Semantic model
QIF
FIWARE
Certification
Data: Set-2022
Editora: Springer
Resumo: The path that the European Commission foresees to leverage data in the best possible way for the sake of European citizens and the digital single market clearly addresses the need for a European Data Space. This data space must follow the rules, derived from European values. The European Data Strategy rests on four pillars: (1) Governance framework for access and use; (2) Investments in Europe’s data capabilities and infrastructures; (3) Competences and skills of individuals and SMEs; (4) Common European Data Spaces in nine strategic areas such as industrial manufacturing, mobility, health, and energy. The project BOOST 4.0 developed a prototype for the industrial manufacturing sector, called European Industrial Data Space (EIDS), an endeavour of 53 companies. The publication will show the developed architectural pattern as well as the developed components and introduce the required infrastructure that was developed for the EIDS. Additionally, the population of such a data space with Big Data enabled services and platforms is described and will be enriched with the perspective of the pilots that have been build based on EIDS.
Descrição: This data driven digital transformation research is also endorsed by the Digital Factory Alliance (DFA)
Peer review: yes
URI: http://hdl.handle.net/10362/150246
DOI: https://doi.org/10.1007/978-3-030-98636-0
ISBN: 978-3-030-98635-3
978-3-030-98636-0
Aparece nas colecções:Home collection (FCT)

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