Pipeline Automation

Pipeline Automation is a methodological framework within data engineering that systematically orchestrates, executes, and monitors data pipeline workflows with minimal human intervention by leveraging predefined rules, scheduling mechanisms, and dependency management to ensure consistent, scalable, and reproducible data processing.

39

Publications

2.5K

Citations

151

Authors

70

Institutions

Publications per year

2017–2026

15

Authors

151

  1. RJ
    Ryan J. Urbanowicz

    University of Pennsylvania, United States

    3 publications · 631 citations

    3

    h-index

  2. JH
    Jason H. Moore

    Dartmouth College, United States

    3 publications · 631 citations

    3

    h-index

  3. RS
    Randal S. Olson

    University of Pennsylvania, United States

    3 publications · 631 citations

    3

    h-index

  4. DE
    David E. Goldberg

    University of Illinois Urbana-Champaign, United States

    2 publications · 82 citations

    2

    h-index

  5. MW
    Martyn Winn

    Daresbury Laboratory, United Kingdom

    2 publications · 345 citations

    2

    h-index

1–5 of 151

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 60 citations

    2

    h-index

  2. Bioinformatics

    2 publications · 75 citations

    2

    h-index

  3. Engineering With Computers

    2 publications · 82 citations

    2

    h-index

  4. 2

    h-index

  5. Current Bioinformatics

    1 publications · 21 citations

    1

    h-index

1–5