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        Designing Data Spaces

        The Ecosystem Approach to Competitive Advantage

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        Contributor(s)
        Otto, Boris (editor)
        ten Hompel, Michael (editor)
        Wrobel, Stefan (editor)
        Language
        English
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        Abstract
        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.
        URI
        https://library.oapen.org/handle/20.500.12657/57901
        Keywords
        Data Spaces; GAIA-X; Data Lakes; Big Data; Information Retrieval; Information Systems Applications; Data Ecosystems; Data Integration; Data Security
        DOI
        10.1007/978-3-030-93975-5
        ISBN
        9783030939755, 9783030939755
        Publisher
        Springer Nature
        Publisher website
        https://www.springernature.com/gp/products/books
        Publication date and place
        Cham, 2022
        Imprint
        Springer
        Classification
        Information technology: general topics
        Databases
        Expert systems / knowledge-based systems
        Information retrieval
        Pages
        580
        Rights
        http://creativecommons.org/licenses/by/4.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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