Data Version Control

Data Version Control is a systematic methodology within data management that tracks and manages changes to datasets over time, distinguishing itself by enabling reproducibility, auditability, and collaborative integrity through structured lineage and version tracking.

69

Publications

3.9K

Citations

326

Authors

147

Institutions

Publications per year

2017–2026

30

Variants

Dvc

Authors

326

  1. AP
    Aditya Parameswaran

    Stanford University, United States

    3 publications · 220 citations

    3

    h-index

  2. CH
    Christos H. Papadimitriou

    University of California, Berkeley, United States

    3 publications · 159 citations

    3

    h-index

  3. PC
    Paris C. Kanellakis

    Brown University, United States

    3 publications · 159 citations

    3

    h-index

  4. GA
    Gopalan Arun

    Oracle (United States), United States

    2 publications · 24 citations

    2

    h-index

  5. LC
    Luciana Conceição de Lima

    Universidade Federal do Rio Grande do Norte, Brazil

    2 publications · 35 citations

    2

    h-index

1–5 of 326

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 3 publications · 205 citations

    3

    h-index

  2. Nature Communications

    2 publications · 414 citations

    2

    h-index

  3. Computers & Geosciences

    CAGEO · 2 publications · 64 citations

    2

    h-index

  4. arXiv (Cornell University)

    Repository · 2 publications · 135 citations

    2

    h-index

  5. Journal of Econometrics

    2 publications · 138 citations

    2

    h-index

1–5