Model-driven Data Design

Model-Driven Data Design is a formal methodology in data modeling that uses high-level conceptual, logical, or physical models as primary artifacts to systematically generate, transform, and manage database schemas and data architectures through automated or semi-automated processes.

9

Publications

276

Citations

47

Authors

31

Institutions

Publications per year

2017–2026

7

Authors

47

  1. JH
    John Hosking

    University of Auckland, New Zealand

    1 publications · 21 citations

    1

    h-index

  2. RA
    Ryan A. Rava

    University at Buffalo, State University of New York, United States

    1 publications · 19 citations

    1

    h-index

  3. QH
    Qiang He

    Swinburne University of Technology, Australia

    1 publications · 21 citations

    1

    h-index

  4. DK
    Dieter Krause

    Hamburg University of Technology, Germany

    1 publications · 18 citations

    1

    h-index

  5. FC
    Felix Chin

    University at Buffalo, State University of New York, United States

    1 publications · 19 citations

    1

    h-index

1–5 of 47

Venues

  1. Epidemics

    1 publications · 39 citations

    1

    h-index

  2. 1

    h-index

  3. Neuroradiology

    1 publications · 19 citations

    1

    h-index

  4. Journal of Computer Languages

    1 publications · 21 citations

    1

    h-index

  5. Systems

    1 publications · 18 citations

    1

    h-index

1–5