This book is is open access which means you have free and unlimited access
Educates data space designers to understand what is required to create a successful data space
Explores the cutting-edge theory, technologies, methodologies, and best practices for data spaces
Captures lessons and experiences in creating data spaces based on real-world projects in various industry sectors
Edward Curry is the Established Professor of Data Science and Director of the Insight SFI Research Centre for Data Analytics at University of Galway, Ireland. Edward has contributed to the foundations of data spaces with contributions to semantics, knowledge graphs, incremental data management, data governance, and multimodal processing. Edward is co-founder and elected Vice President of the Big Data Value Association, an industry-led European big data community.
Simon Scerri has over 15 years of research experience exploring Knowledge Graph methodologies and applications, with the objective of strengthening and diversifying Data Value Chains to realise various data infrastructures. Currently, Simon fulfils the role of a senior technical consultant at metaphacts GmbH, Germany. Previously, Simon fronted the Knowledge Graph competency area at the Enterprise Information Systems department in Fraunhofer IAIS.
Tuomo Tuikka is the Lead of Data Space Solutions at VTT Technical Research Centre of Finland. He is involved in many European and national research and innovation activities especially on data spaces, data infrastructures, big data, and artificial intelligence. Tuomo is a member of the Board of the Big Data Value Association, the Gaia-X Finland hub steering group, and leads the data analytics spearhead program at the city of Oulu.
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.
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.
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.
Open Access This book is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this book are included in the book's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the book's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
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.
Edward Curry is the Established Professor of Data Science and Director of the Insight SFI Research Centre for Data Analytics at University of Galway, Ireland. Edward has contributed to the foundations of data spaces with contributions to semantics, knowledge graphs, incremental data management, data governance, and multimodal processing. Edward is co-founder and elected Vice President of the Big Data Value Association, an industry-led European big data community.
Simon Scerri has over 15 years of research experience exploring Knowledge Graph methodologies and applications, with the objective of strengthening and diversifying Data Value Chains to realise various data infrastructures. Currently, Simon fulfils the role of a senior technical consultant at metaphacts GmbH, Germany. Previously, Simon fronted the Knowledge Graph competency area at the Enterprise Information Systems department in Fraunhofer IAIS.
Tuomo Tuikka is the Lead of Data Space Solutions at VTT Technical Research Centre of Finland. He is involved in many European and national research and innovation activities especially on data spaces, data infrastructures, big data, and artificial intelligence. Tuomo is a member of the Board of the Big Data Value Association, the Gaia-X Finland hub steering group, and leads the data analytics spearhead program at the city of Oulu.
Über den Autor
Edward Curry is the Established Professor of Data Science and Director of the Insight SFI Research Centre for Data Analytics at University of Galway, Ireland. Edward has contributed to the foundations of data spaces with contributions to semantics, knowledge graphs, incremental data management, data governance, and multimodal processing. Edward is co-founder and elected Vice President of the Big Data Value Association, an industry-led European big data community.
rn
Simon Scerri has over 15 years of research experience exploring Knowledge Graph methodologies and applications, with the objective of strengthening and diversifying Data Value Chains to realise various data infrastructures. Currently, Simon fulfils the role of a senior technical consultant at metaphacts GmbH, Germany. Previously, Simon fronted the Knowledge Graph competency area at the Enterprise Information Systems department in Fraunhofer IAIS.
rn
Tuomo Tuikka is the Lead of Data Space Solutions at VTT Technical Research Centre of Finland. He is involved in many European and national research and innovation activities especially on data spaces, data infrastructures, big data, and artificial intelligence. Tuomo is a member of the Board of the Big Data Value Association, the Gaia-X Finland hub steering group, and leads the data analytics spearhead program at the city of Oulu.
Inhaltsverzeichnis
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.
Klappentext
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.nThe 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. nThe 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.nThe 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.nThe 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.nnnThe 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.
This book is is open access which means you have free and unlimited access
Educates data space designers to understand what is required to create a successful data space
Explores the cutting-edge theory, technologies, methodologies, and best practices for data spaces
Captures lessons and experiences in creating data spaces based on real-world projects in various industry sectors
