Temporal Data Warehousing

Temporal Data Warehousing is a data warehousing paradigm that integrates temporal database principles to systematically model, store, and manage historical and time-varying data for analytical processing, distinguishing itself by explicitly supporting time as a first-class dimension for query, analysis, and schema evolution.

34

Publications

1.3K

Citations

73

Authors

34

Institutions

Publications per year

2017–2026

3

Authors

73

  1. CK
    Christian Koncilia

    Institute for Interdisciplinary Studies of Austrian Universities, Austria

    3 publications · 66 citations

    3

    h-index

  2. JE
    Johann Eder

    University of Klagenfurt, Austria

    2 publications · 51 citations

    2

    h-index

  3. MG
    Matteo Golfarelli

    University of Bologna, Italy

    2 publications · 122 citations

    2

    h-index

  4. EZ
    Esteban Zimányi

    Université Libre de Bruxelles, Belgium

    2 publications · 88 citations

    2

    h-index

  5. BS
    Bernhard Seeger

    Philipps University of Marburg, Germany

    2 publications · 110 citations

    2

    h-index

1–5 of 73

Venues

  1. Data & Knowledge Engineering

    DKE · 3 publications · 98 citations

    3

    h-index

  2. International Journal of Data Warehousing and Mining

    IJDWM · 2 publications · 128 citations

    2

    h-index

  3. ACM Transactions on Database Systems

    TODS · 1 publications · 31 citations

    1

    h-index

  4. 1

    h-index

  5. Issues in Information Systems

    1 publications · 12 citations

    1

    h-index

1–5