Competence as enabler of urban critical infrastructure resilience assessment.

Abstract

Die Autoren diskutieren die Schwierigkeiten bei der Entwicklung von Resilienzindikatoren und stellen relevante Qualitätskriterien für ihre Bewertung und Auswahl vor.Providers of urban critical infrastructures are often relying on indicator-based approaches for resilience management. While science is developing more and more intelligent resilience indicators, the application and interpretation of such indicators might lead to new challenges and questions. Since models always reduce the complexity of real world systems, users of the developed indicators need to understand the underlying assumptions. Otherwise, simplifications may lead to misinterpretations and severe consequences for the infrastructure providers and the society. In this chapter the authors discuss the difficulties related to the development usage of resilience indictors and present relevant quality criteria for their evaluation and selection. Additionally, proper resilience assessment requires expert skills and an advanced knowledge and competence profile. Bloom's learning taxonomy provides the theoretical underpinning which may be used to develop such profiles.