TY  - BOOK
AU  - Curry,Edward
AU  - Metzger,Andreas
AU  - Zillner,Sonja
AU  - Pazzaglia,Jean-Christophe
AU  - García Robles,Ana
ED  - SpringerLink (Online service)
TI  - The Elements of Big Data Value: Foundations of the Research and Innovation Ecosystem 
SN  - 9783030681760
AV  - QA75.5-76.95 
U1  - 025.04 23
PY  - 2021///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Information storage and retrieval systems
KW  - Technological innovations
KW  - Computer industry
KW  - Big data
KW  - Information Storage and Retrieval
KW  - Innovation and Technology Management
KW  - Technology Commercialization
KW  - The Computer Industry
KW  - Big Data
N1  - Part I: Ecosystem Elements of Big Data Value -- The European Big Data Value Ecosystem -- Stakeholder Analysis of Data Ecosystems -- A Roadmap to Drive Adoption of Data Ecosystems -- Achievements and Impact of the Big Data Value Public-Private Partnership: The Story so Far -- Part II: Research and Innovation Elements of Big Data Value -- Technical Research Priorities for Big Data -- A Reference Model for Big Data Technologies -- Data Protection in the Era of Artificial Intelligence: Trends, Existing Solutions and Recommendations for Privacy-Preserving Technologies -- A Best Practice Framework for Centres of Excellence in Big Data and Artificial Intelligence -- Data Innovation Spaces -- Part III: Business, Policy, and Societal Elements of Big Data Value -- Big Data Value Creation by Example -- Business Models and Ecosystem for Big Data -- Innovation in Times of Big Data and AI: Introducing the Data-Driven Innovation (DDI) Framework -- The Road to Big Data Standardisation -- The Role of Data Regulation in Shaping AI: An Overview of Challenges and Recommendations for SMEs -- Part IV: Emerging Elements of Big Data Value -- Data Economy 2.0: From Big Data Value to AI Value and a European Data Space; Open Access
N2  - 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.
UR  - https://doi.org/10.1007/978-3-030-68176-0
ER  -