Data Provenance Modeling

Data Provenance Modeling is a formal method for systematically representing the origin, lineage, and transformation history of data within an information system, distinguishing itself by enabling traceability, accountability, and trustworthiness assessment through structured metadata and dependency relationships.

177

Publications

7.7K

Citations

539

Authors

226

Institutions

Publications per year

2017–2026

42

Authors

539

  1. LM
    Luc Moreau

    University of Southampton, United Kingdom

    9 publications · 260 citations

    9

    h-index

  2. PG
    Paul Groth

    University of Amsterdam, Netherlands

    8 publications · 460 citations

    8

    h-index

  3. SS
    Satya S. Sahoo

    Case Western Reserve University, United States

    8 publications · 575 citations

    8

    h-index

  4. JC
    James Cheney

    University of Edinburgh, United Kingdom

    7 publications · 900 citations

    7

    h-index

  5. SM
    Simon Miles

    King's College London, United Kingdom

    7 publications · 416 citations

    7

    h-index

1–5 of 539

Venues

  1. 7

    h-index

  2. Future Generation Computer Systems

    FGCS · 5 publications · 100 citations

    5

    h-index

  3. ePrints Soton (University of Southampton)

    Repository · 5 publications · 324 citations

    5

    h-index

  4. Research Explorer (The University of Manchester)

    Repository · 3 publications · 286 citations

    3

    h-index

  5. IEEE Internet Computing

    3 publications · 90 citations

    3

    h-index

1–5