Data Dependency Tracking

Data Dependency Tracking is a data management method that systematically identifies, records, and analyzes the relationships and transformations among data elements across processing stages to establish traceability in data flows within data lineage and orchestration systems.

20

Publications

530

Citations

64

Authors

28

Institutions

Publications per year

2017–2026

4

Authors

64

  1. HY
    Heon Y. Yeom

    Seoul National University, South Korea

    2 publications · 79 citations

    2

    h-index

  2. TP
    Tae‐Soon Park

    Korea Research Institute of Standards and Science, South Korea

    2 publications · 79 citations

    2

    h-index

  3. WZ
    Willy Zwaenepoel

    Rice University, United States

    2 publications · 37 citations

    2

    h-index

  4. GP
    Geoffrey Poore

    Union University, United States

    1 publications · 14 citations

    1

    h-index

  5. MK
    Morry Katz

    Rockwell Automation (United States), United States

    1 publications · 35 citations

    1

    h-index

1–5 of 64

Venues

  1. Infoscience (Ecole Polytechnique Fédérale de Lausanne)

    Repository · 1 publications · 10 citations

    1

    h-index

  2. Computational Science & Discovery

    CSD · 1 publications · 14 citations

    1

    h-index

  3. 1

    h-index

  4. Water

    1 publications · 15 citations

    1

    h-index

  5. Future Generation Computer Systems

    FGCS · 1 publications · 16 citations

    1

    h-index

1–5