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This project includes a survey instrument, data, and annual census reports from the National Science Foundation (NSF)-funded Social Science Extreme Events Research (SSEER) network, which is headquartered at the Natural Hazards Engineering Research Infrastructure (NHERI) CONVERGE facility at the Natural Hazards Center at the University of Colorado Boulder. The SSEER network, which was launched in 2018, was formed, in part, to respond to the need for more specific information about the status and expertise of the social science hazards and disaster research workforce. The mission of SSEER is to identify and map social scientists involved in hazards and disaster research in order to highlight their expertise and connect social science researchers to one another, to interdisciplinary teams, and to communities at risk to hazards and affected by disasters. Ultimately, the goals of SSEER are to amplify the contributions of social scientists and to advance the field through expanding the available social science evidence base. To see the SSEER map and to learn more about the SSEER initiative, please visit: https://converge.colorado.edu/research-networks/sseer. All social and behavioral scientists and those in allied disciplines who study the human, economic, policy, and health dimensions of disasters are invited to join this network via a short online survey. This DesignSafe project includes: (1) the SSEER survey instrument; (2) de-identified data, which is updated annually as new researchers join the SSEER network and returning members update their information; and (3) SSEER annual census reports. These resources are available to all who are interested in learning more about the composition of the social science hazards and disaster workforce. SSEER is part of a larger ecosystem of NSF-funded extreme events research and reconnaissance networks designed to help coordinate disciplinary communities in engineering and the sciences, while also encouraging cross-disciplinary information sharing and interdisciplinary integration. To learn more about the networks and research ecosystem, please visit: https://converge.colorado.edu/research-networks/.
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Integrative Interdisciplinary Approaches to Critical Infrastructure Interdependency Analysis
Abstract There is a growing understanding that cross‐sector risks faced by critical infrastructure assets in natural disasters require a collaborative foresight from multiple disciplines. However, current contributions to infrastructure interdependency analysis remain centered in discipline‐specific methodologies often constrained by underlying theories and assumptions. This perspective article contributes to ongoing discussions about the uses, challenges, and opportunities provided by interdisciplinary research in critical infrastructure interdependency analysis. In doing so, several modes of integration of computational modeling with contributions from the social sciences and other disciplines are explored to advance knowledge that can improve the infrastructure system resilience under extreme events. Three basic modes of method integration are identified and discussed: (a) integrating engineering models and social science research, (b) engaging communities in participative and collaborative forms of social learning and problem solving using simulation models to facilitate synthesis, exploration, and evaluation of scenarios, and (c) developing interactive simulations where IT systems and humans act as “peers” leveraging the capacity of distributed networked platforms and human‐in‐the‐loop architectures for improving situational awareness, real‐time decision making, and response capabilities in natural disasters. Depending on the conceptualization of the issues under investigation, these broadly defined modes of integration can coalesce to address key issues in promoting interdisciplinary research by outlining potential areas of future inquiry that would be most beneficial to the critical infrastructure protection communities.
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- Award ID(s):
- 1541089
- PAR ID:
- 10061172
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Risk Analysis
- Volume:
- 41
- Issue:
- 7
- ISSN:
- 0272-4332
- Page Range / eLocation ID:
- p. 1111-1117
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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