Viewing urban disruptions from a decision informatics perspective

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

Urban infrastructures are the focus of terrorist acts because, quite simply, they produce the most visible impact, if not casualties. While terrorist acts are the most insidious and onerous of all disruptions, it is obvious that there are many similarities to the way one should deal with these willful acts and those caused by natural and accidental incidents that have also resulted in adverse and severe consequences. However, there is one major and critical difference between terrorist acts and the other types of disruptions: the terrorist acts are willful — and therefore also adaptive, if not coordinated. One must counter these acts with the same, if not more sophisticated, willful, adaptive and informed approach. Real-time, information-based decision making — which Tien (2003) has called the decision informatics paradigm — is the approach advanced herein to help make the right decisions at the various stages of a disruption. It is focused on decisions and based on multiple data sources, data fusion and analysis methods, timely information, stochastic decision models and a systems engineering outlook; moreover, it is multidisciplinary, evolutionary and systemic in practice. The approach provides a consistent way to address real-time emergency issues, including those concerned with the preparation for a major disruption, the prediction of such a disruption, the prevention or mitigation of the disruption, the detection of the disruption, the response to the disruption, and the recovery steps that are necessary to adequately, if not fully, recuperate from the disruption. The efforts of the U. S. Department of Homeland Security and its academically-based Homeland Security Centers of Excellence are considered within the proposed types, stages and decisions framework.

Original languageEnglish (US)
Pages (from-to)257-288
Number of pages32
JournalJournal of Systems Science and Systems Engineering
Volume14
Issue number3
DOIs
StatePublished - Sep 1 2005
Externally publishedYes

Keywords

  • Data fusion
  • adaptive algorithms
  • data analysis
  • decision modeling
  • systems engineering

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems

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