Title: Infrastructure modelling 2.0

Authors: Chris Davis, Igor Nikolic, Gerard P.J. Dijkema

Addresses: Section Energy and Industry, Faculty of Technology, Policy and Management, Delft University of Technology, Jaffalaan 5, 2628 BX, Delft, The Netherlands. ' Section Energy and Industry, Faculty of Technology, Policy and Management, Delft University of Technology, Jaffalaan 5, 2628 BX, Delft, The Netherlands. ' Section Energy and Industry, Faculty of Technology, Policy and Management, Delft University of Technology, Jaffalaan 5, 2628 BX, Delft, The Netherlands

Abstract: To support stakeholders involved in infrastructure development, we develop evolutionary models of these complex systems, which is a formidable task with respect to data requirements, information representation and knowledge management. Re-addressing a case on bio-electricity infrastructure evolution, we demonstrate first a series of visualisations of economic and ecologic system parameters as they change during infrastructure development over simulated decades. This setup allows us to demonstrate to stakeholders a means to anticipate the consequences of decisions on (dis)investment of power generation options available. In developing these tools, our approach needed to be expanded to better handle the complexity of infrastructure systems, due to the multiple relevant social and technical contexts from which these systems need to be considered. The second part of this paper describes our work on enabling collaborative mapping of our knowledge of infrastructure systems to help integrate diverse types of knowledge. Current internet-enabled developments such as Web 2.0 and the Semantic Web offer tremendous scope to lower the transaction cost of gathering and assembling data. Already, these are changing the ways scientific collaboration is conducted. Finally, we suggest to connect this to evolutionary models to elucidate the dynamics of these systems.

Keywords: agent-based modelling; ABM; complexity; bioelectricity infrastructures; information technology; infrastructure modelling; critical infrastructures; evolutionary modelling; agent-based systems; multi-agent systems; MAS; visualisation; power generation options; system dynamics; Web 2.0; semantic web.

DOI: 10.1504/IJCIS.2010.031073

International Journal of Critical Infrastructures, 2010 Vol.6 No.2, pp.168 - 186

Published online: 20 Jan 2010 *

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