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    The Elements of Big Data Value

    Foundations of the Research and Innovation Ecosystem

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    Contributor(s)
    Curry, Edward (editor)
    Metzger, Andreas (editor)
    Zillner, Sonja (editor)
    Pazzaglia, Jean-Christophe (editor)
    García Robles, Ana (editor)
    Language
    English
    Show full item record
    Abstract
    This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.
    URI
    https://library.oapen.org/handle/20.500.12657/50023
    Keywords
    Information Storage and Retrieval; Business and Management, general; Innovation/Technology Management; The Computer Industry; Big Data; Innovation and Technology Management; Technology Commercialization; Digital Transformation; Innovation Spaces; Data-Driven Innovation; Data Analytics; Technology Management; Data Ecosystems; Data Protection; Big Data Business Models; Open Access; Information retrieval; Data warehousing; Business & Management; Research & development management; Industrial applications of scientific research & technological innovation; Information technology industries; Databases
    DOI
    10.1007/978-3-030-68176-0
    ISBN
    9783030681760, 9783030681760
    Publisher
    Springer Nature
    Publisher website
    https://www.springernature.com/gp/products/books
    Publication date and place
    2021
    Grantor
    • National University of Ireland - [grantnumber unknown]
    Imprint
    Springer International Publishing
    Classification
    Information retrieval
    Business and Management
    Research and development management
    Information technology industries
    Databases
    Pages
    399
    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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