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International Conference on Future Data and Security Engineering

FDSE 2021: Future Data and Security Engineering pp 23–35Cite as

Time in Data Models

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 13076))

Abstract

Time is an essential dimension of our perception of the world and hence an important dimension for the representation of the real and social world in data models. We give an overview of the basics of representing time in data models and representing objects and processes with respect to the temporal dimension. In particular, we discuss basic concepts and novel developments in the areas of representing time, snapshot data models versus temporal versioning of data models, time-related storage of data in databases, temporal data warehouses and databases, schema evolution, and the representation and checking of temporal integrity constraints.

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Authors and Affiliations

  1. Department of Informatics-Systems, Universität Klagenfurt, Klagenfurt, Austria

    Johann Eder, Marco Franceschetti & Josef Lubas

Authors
  1. Johann Eder
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  2. Marco Franceschetti
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  3. Josef Lubas
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Corresponding author

Correspondence to Johann Eder .

Editor information

Editors and Affiliations

  1. HCMC University of Technology, Ho Chi Minh City, Vietnam

    Tran Khanh Dang

  2. Johannes Kepler University of Linz, Linz, Austria

    Josef Küng

  3. Sungkyunkwan University, Suwon, Korea (Republic of)

    Tai M. Chung

  4. Hosei University, Koganei-shi, Tokyo, Japan

    Makoto Takizawa

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Eder, J., Franceschetti, M., Lubas, J. (2021). Time in Data Models. In: Dang, T.K., Küng, J., Chung, T.M., Takizawa, M. (eds) Future Data and Security Engineering. FDSE 2021. Lecture Notes in Computer Science(), vol 13076. Springer, Cham. https://doi.org/10.1007/978-3-030-91387-8_2

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  • DOI: https://doi.org/10.1007/978-3-030-91387-8_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-91386-1

  • Online ISBN: 978-3-030-91387-8

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