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Empirical Foundations of Information and Software Science V pp 29–37Cite as

Methodological Principles of Uncertainty in Information Systems Modeling

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Abstract

System modeling permeates all disciplines of science, both natural and artificial. The general concepts of system modeling are presented in summary fashion. The key role of uncertainty in system modeling is discussed including the principles of maximum and minimum uncertainty. Recent results regarding conceptualization of uncertainty, which demonstrate that uncertainty is a multidimensional concept, are overviewed, and the implications for modeling in information and software engineering are discussed.

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Author information

Authors and Affiliations

  1. Department of Systems Science Thomas J. Watson School, State University of New York, Binghamton, New York, 13903, USA

    George J. Klir

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  1. George J. Klir
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Editor information

Editors and Affiliations

  1. School of Information and Computer Science, Georgia Institute of Technology, Atlanta, Georgia, USA

    Pranas Zunde

  2. U.S. Army Institute for Research in Management Information, Communications, and Computer Science, Atlanta, Georgia, USA

    Dan Hocking

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© 1990 Plenum Press, New York

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Klir, G.J. (1990). Methodological Principles of Uncertainty in Information Systems Modeling. In: Zunde, P., Hocking, D. (eds) Empirical Foundations of Information and Software Science V. Springer, Boston, MA. https://doi.org/10.1007/978-1-4684-5862-6_4

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  • DOI: https://doi.org/10.1007/978-1-4684-5862-6_4

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4684-5864-0

  • Online ISBN: 978-1-4684-5862-6

  • eBook Packages: Springer Book Archive

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