Federated Data Sharing

Federated Data Sharing is a secure data sharing paradigm in which multiple entities collaboratively access and analyze distributed datasets without transferring raw data, preserving data sovereignty and privacy by keeping data localized while enabling integrated query processing or model training across decentralized sources.

112

Publications

7.3K

Citations

687

Authors

316

Institutions

Publications per year

2017–2026

93

Authors

687

  1. SG
    Song Guo

    Hong Kong Polytechnic University, Hong Kong SAR China

    3 publications · 74 citations

    3

    h-index

  2. YH
    Yongfeng Huang

    Tsinghua University, China

    2 publications · 70 citations

    2

    h-index

  3. SG
    Suyu Ge

    Tsinghua University, China

    2 publications · 70 citations

    2

    h-index

  4. TN
    Tommi Nyrönen

    CSC - IT Center for Science (Finland), Finland

    2 publications · 88 citations

    2

    h-index

  5. PG
    Peter Gibbs

    The Royal Melbourne Hospital, Australia

    2 publications · 35 citations

    2

    h-index

1–5 of 687

Venues

  1. IEEE Internet of Things Journal

    8 publications · 649 citations

    8

    h-index

  2. arXiv (Cornell University)

    Repository · 6 publications · 208 citations

    6

    h-index

  3. IEEE Transactions on Industrial Informatics

    5 publications · 614 citations

    5

    h-index

  4. PubMed

    Repository · 3 publications · 58 citations

    3

    h-index

  5. Journal of the American Medical Informatics Association

    JAMIA · 3 publications · 214 citations

    3

    h-index

1–5