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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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