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Data spacesdesign, deployment and future directions /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data spacesedited by Edward Curry, Simon Scerri, Tuomo Tuikka.
其他題名:	design, deployment and future directions /
其他作者:	Scerri, Simon.
出版者:	Cham :Springer International Publishing :2022.
面頁冊數:	xx, 357 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Database design.
電子資源:	https://doi.org/10.1007/978-3-030-98636-0
ISBN:	9783030986360$q(electronic bk.)

Data spacesdesign, deployment and future directions /
Data spacesdesign, deployment and future directions /[electronic resource] :edited by Edward Curry, Simon Scerri, Tuomo Tuikka. - Cham :Springer International Publishing :2022. - xx, 357 p. :ill. (some col.), digital ;24 cm.

Data Spaces: Design, Deployment, and Future Directions -- Part I: Design -- An Organizational Maturity Model for Data Spaces: A Data Sharing Wheel Approach -- Data Platforms for Data Spaces -- Technological Perspective of Data Governance in Data Space Ecosystems -- Increasing Trust for Data Spaces with Federated Learning -- KRAKEN: A Secure, Trusted, Regulatory-Compliant, and Privacy-Preserving Data Sharing Platform -- Connecting Data Spaces and Data Marketplaces and the Progress Toward the European Single Digital Market with Open-Source Software -- AI-Based Hybrid Data Platforms -- Part II: Deployment -- A Digital Twin Platform for Industrie 4.0 -- A Framework for Big Data Sovereignty: The European Industrial Data Space (EIDS) -- Deploying a Scalable Big Data Platform to Enable a Food Safety Data Space -- Data Space Best Practices for Data Interoperability in FinTechs -- TIKD: A Trusted Integrated Knowledge Dataspace for Sensitive Data Sharing and Collaboration -- Toward an Energy Data Platform Design: Challenges and Perspectives from the SYNERGY Big Data Platform and AI Analytics Marketplace -- Part III: Future Directions -- Privacy-Preserving Techniques for Trustworthy Data Sharing: Opportunities and Challenges for Future Research -- Common European Data Spaces: Challenges and Opportunities.

Open Access

This open access book aims to educate data space designers to understand what is required to create a successful data space. It explores cutting-edge theory, technologies, methodologies, and best practices for data spaces for both industrial and personal data and provides the reader with a basis for understanding the design, deployment, and future directions of data spaces. The book captures the early lessons and experience in creating data spaces. It arranges these contributions into three parts covering design, deployment, and future directions respectively. The first part explores the design space of data spaces. The single chapters detail the organisational design for data spaces, data platforms, data governance federated learning, personal data sharing, data marketplaces, and hybrid artificial intelligence for data spaces. The second part describes the use of data spaces within real-world deployments. Its chapters are co-authored with industry experts and include case studies of data spaces in sectors including industry 4.0, food safety, FinTech, health care, and energy. The third and final part details future directions for data spaces, including challenges and opportunities for common European data spaces and privacy-preserving techniques for trustworthy data sharing. The book is of interest to two primary audiences: first, researchers interested in data management and data sharing, and second, practitioners and industry experts engaged in data-driven systems where the sharing and exchange of data within an ecosystem are critical.

ISBN: 9783030986360$q(electronic bk.)

Standard No.: 10.1007/978-3-030-98636-0doiSubjects--Topical Terms:

184445
Database design.

LC Class. No.: QA76.9.D26 / D37 2022

Dewey Class. No.: 005.743

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505 0 $a Data Spaces: Design, Deployment, and Future Directions -- Part I: Design -- An Organizational Maturity Model for Data Spaces: A Data Sharing Wheel Approach -- Data Platforms for Data Spaces -- Technological Perspective of Data Governance in Data Space Ecosystems -- Increasing Trust for Data Spaces with Federated Learning -- KRAKEN: A Secure, Trusted, Regulatory-Compliant, and Privacy-Preserving Data Sharing Platform -- Connecting Data Spaces and Data Marketplaces and the Progress Toward the European Single Digital Market with Open-Source Software -- AI-Based Hybrid Data Platforms -- Part II: Deployment -- A Digital Twin Platform for Industrie 4.0 -- A Framework for Big Data Sovereignty: The European Industrial Data Space (EIDS) -- Deploying a Scalable Big Data Platform to Enable a Food Safety Data Space -- Data Space Best Practices for Data Interoperability in FinTechs -- TIKD: A Trusted Integrated Knowledge Dataspace for Sensitive Data Sharing and Collaboration -- Toward an Energy Data Platform Design: Challenges and Perspectives from the SYNERGY Big Data Platform and AI Analytics Marketplace -- Part III: Future Directions -- Privacy-Preserving Techniques for Trustworthy Data Sharing: Opportunities and Challenges for Future Research -- Common European Data Spaces: Challenges and Opportunities.
506 0 $a Open Access
520 $a This open access book aims to educate data space designers to understand what is required to create a successful data space. It explores cutting-edge theory, technologies, methodologies, and best practices for data spaces for both industrial and personal data and provides the reader with a basis for understanding the design, deployment, and future directions of data spaces. The book captures the early lessons and experience in creating data spaces. It arranges these contributions into three parts covering design, deployment, and future directions respectively. The first part explores the design space of data spaces. The single chapters detail the organisational design for data spaces, data platforms, data governance federated learning, personal data sharing, data marketplaces, and hybrid artificial intelligence for data spaces. The second part describes the use of data spaces within real-world deployments. Its chapters are co-authored with industry experts and include case studies of data spaces in sectors including industry 4.0, food safety, FinTech, health care, and energy. The third and final part details future directions for data spaces, including challenges and opportunities for common European data spaces and privacy-preserving techniques for trustworthy data sharing. The book is of interest to two primary audiences: first, researchers interested in data management and data sharing, and second, practitioners and industry experts engaged in data-driven systems where the sharing and exchange of data within an ecosystem are critical.
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