Designing Data Spaces - The Ecosystem Approach to Competitive Advantage (Paperback, 1st ed. 2022)

This open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is structured in four parts: Part I "Foundations and Contexts" provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II "Data Space Technologies" subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various "Use Cases and Data Ecosystems" from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several "Solutions and Applications", eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more. Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Release date:	July 2022
Editors:	Boris Otto • Michael ten Hompel • Stefan Wrobel
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	580
Edition:	1st ed. 2022
ISBN-13:	978-3-03-093977-9
Categories:	Books > Computing & IT > Applications of computing > Databases > General Books > Computing & IT > Applications of computing > Artificial intelligence > Knowledge-based systems / expert systems Promotions
LSN:	3-03-093977-4
Barcode:	9783030939779

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