Defining resilience analytics for interdependent cyber-physical-social networks

Kash Barker, James H. Lambert, Christopher W. Zobel, Andrea H. Tapia, Jose E. Ramirez-Marquez, Laura Albert, Charles D. Nicholson, Cornelia Caragea

Research output: Contribution to journalArticlepeer-review

71 Scopus citations

Abstract

Theory, methodology, and applications of risk analysis contribute to the quantification and management of resilience. For risk analysis, numerous complementary frameworks, guidelines, case studies, etc., are available in the literature. For resilience, the documented applications are sparse relative to numerous untested definitions and concepts. This essay on resilience analytics motivates the methodology, tools, and processes that will achieve resilience of real systems. The paper describes how risk analysts will lead in the modeling, quantification, and management of resilience for a variety of systems subject to future conditions, including technologies, economics, environment, health, developing regions, regulations, etc. The paper identifies key gaps where methods innovations are needed, presenting resilience of interdependent infrastructure networks as an example. Descriptive, predictive, and prescriptive analytics are differentiated. A key outcome will be the recognition, adoption, and advancement of resilience analytics by scholars and practitioners of risk analysis.

Original languageEnglish (US)
Pages (from-to)59-67
Number of pages9
JournalSustainable and Resilient Infrastructure
Volume2
Issue number2
DOIs
StatePublished - Apr 3 2017

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Geography, Planning and Development
  • Building and Construction
  • Safety, Risk, Reliability and Quality

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