Data Flow Patterns

Data Flow Patterns is a formal model that specifies recurring structures and behaviors in the movement, transformation, and synchronization of data within workflow systems, distinguishing it from other workflow design elements by its focus on the systematic representation of data interactions across processing stages.

753

Publications

42.8K

Citations

2.2K

Authors

681

Institutions

Publications per year

2017–2026

174

Authors

2.2K

  1. WM
    Wil M. P. van der Aalst

    Eindhoven University of Technology, Netherlands

    13 publications · 2.7K citations

    12

    h-index

  2. ML
    Mary Lou Soffa

    University of Pittsburgh, United States

    10 publications · 704 citations

    10

    h-index

  3. MJ
    Mary Jean Harrold

    Georgia Institute of Technology, United States

    10 publications · 1K citations

    10

    h-index

  4. AH
    Arthur H. M. ter Hofstede

    Queensland University of Technology, Australia

    9 publications · 2.4K citations

    9

    h-index

  5. RG
    Rajiv Gupta

    University of California, Riverside, United States

    7 publications · 552 citations

    7

    h-index

1–5 of 2.2K

Venues

  1. IEEE Transactions on Software Engineering

    TSE · 14 publications · 4.2K citations

    13

    h-index

  2. Future Generation Computer Systems

    FGCS · 8 publications · 248 citations

    8

    h-index

  3. ACM SIGPLAN Notices

    8 publications · 541 citations

    8

    h-index

  4. Computer

    7 publications · 773 citations

    7

    h-index

  5. IEEE Access

    6 publications · 307 citations

    6

    h-index

1–5