Rethinking Network Science and Modeling for Critical Infrastructure Protection, Analysis, and Development: Difference between revisions
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{{Rethinking Network Science and Modeling for Critical Infrastructure Protection, Analysis, and Development}} | {{Rethinking Network Science and Modeling for Critical Infrastructure Protection, Analysis, and Development}} | ||
organized by Cris Moore, Paul Hines, Matthew Koehler<br> | ''organized by '''Cris Moore''', '''Paul Hines''', and '''Matthew Koehler'''''<br> | ||
Our nation’s, and indeed all of human society’s, dependence on infrastructure continues to grow. Unfortunately, our ability to analyze, model, and understand our infrastructure is not keeping pace with this growing dependence. How do we prioritize limited investment capital? How do we prioritize protection? How do we forecast changes over time, as a population’s density changes, and as cultural/historical idiosyncrasies develop? In general, it is straight forward to represent an infrastructure system, or even multiple interconnected infrastructure systems, as a network. However, simple applications of network science do not necessarily produce useful insight, and may be premised upon faulty assumptions of cause and effect, and how effects spread. This workshop is a follow-on to the May 2012 workshop "Power Grids as Complex Networks: Formulating Problems for Useful Science and Science-Based Engineering", held at SFI. We will attempt to formulate the requirements of a network science that can handle the complexities of infrastructure networks, especially the power grid, and begin to tackle the related question of when a model of infrastructure is “simple enough” to be useful but not so simple as to be misleading. | Our nation’s, and indeed all of human society’s, dependence on infrastructure continues to grow. Unfortunately, our ability to analyze, model, and understand our infrastructure is not keeping pace with this growing dependence. How do we prioritize limited investment capital? How do we prioritize protection? How do we forecast changes over time, as a population’s density changes, and as cultural/historical idiosyncrasies develop? In general, it is straight forward to represent an infrastructure system, or even multiple interconnected infrastructure systems, as a network. However, simple applications of network science do not necessarily produce useful insight, and may be premised upon faulty assumptions of cause and effect, and how effects spread. This workshop is a follow-on to the May 2012 workshop "Power Grids as Complex Networks: Formulating Problems for Useful Science and Science-Based Engineering", held at SFI. We will attempt to formulate the requirements of a network science that can handle the complexities of infrastructure networks, especially the power grid, and begin to tackle the related question of when a model of infrastructure is “simple enough” to be useful but not so simple as to be misleading. | ||
Latest revision as of 15:04, 4 September 2013
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organized by Cris Moore, Paul Hines, and Matthew Koehler
Our nation’s, and indeed all of human society’s, dependence on infrastructure continues to grow. Unfortunately, our ability to analyze, model, and understand our infrastructure is not keeping pace with this growing dependence. How do we prioritize limited investment capital? How do we prioritize protection? How do we forecast changes over time, as a population’s density changes, and as cultural/historical idiosyncrasies develop? In general, it is straight forward to represent an infrastructure system, or even multiple interconnected infrastructure systems, as a network. However, simple applications of network science do not necessarily produce useful insight, and may be premised upon faulty assumptions of cause and effect, and how effects spread. This workshop is a follow-on to the May 2012 workshop "Power Grids as Complex Networks: Formulating Problems for Useful Science and Science-Based Engineering", held at SFI. We will attempt to formulate the requirements of a network science that can handle the complexities of infrastructure networks, especially the power grid, and begin to tackle the related question of when a model of infrastructure is “simple enough” to be useful but not so simple as to be misleading.