Data Convergence

Data Convergence is a data synchronization framework that integrates heterogeneous, distributed datasets into a unified, consistent state through iterative transformation and reconciliation processes, ensuring semantic and temporal alignment across disparate sources.

52

Publications

5.1K

Citations

193

Authors

107

Institutions

Publications per year

2017–2026

18

Authors

193

  1. CM
    Clayton Miller

    National University of Singapore, Singapore

    2 publications · 77 citations

    2

    h-index

  2. AM
    Alan Mackay‐Sim

    Griffith University, Australia

    1 publications · 102 citations

    1

    h-index

  3. HJ
    Hideyuki Jitsumoto

    Tokyo Institute of Technology, Japan

    1 publications · 14 citations

    1

    h-index

  4. GO
    Gérald Oster

    Icahn School of Medicine at Mount Sinai, United States

    1 publications · 68 citations

    1

    h-index

  5. AA
    Arnold Adimabua Ojugo

    Federal University of Petroleum Resource Effurun, Nigeria

    1 publications · 26 citations

    1

    h-index

1–5 of 193

Venues

  1. Figshare

    Repository · 2 publications · 46 citations

    2

    h-index

  2. IEEE Communications Magazine

    2 publications · 149 citations

    2

    h-index

  3. Computers & Chemical Engineering

    2 publications · 181 citations

    2

    h-index

  4. IEEE Access

    2 publications · 32 citations

    2

    h-index

  5. 1

    h-index

1–5