Abstract

This article discusses a dashboard toolkit designed at the Knowledge Exchange for Resilience at the Arizona State University to integrate and analyze multi-agency data offering many ways of visualizing big data representable, contextualizable, and intelligible to a non-expert target audience. We outline a community-driven approach to identify pressing resiliency issues and deploy dashboard tools on targeted areas for significant community benefit. Our research builds on the offerings of data science to aid community-focused decision support systems to enable evidence-based and real-time decision-making. We hypothesize that building community resilience in response to emerging challenges requires a combination of timely data at the local scale and easy-to-use decision support tools. This research particularly focuses on augmenting the capacity of communities through dashboard technologies to comprehend rapidly evolving issues and address them in a timely and efficient manner. Our work contributes to a rapidly growing research domain around geospatial data visualization technologies that are increasingly playing a vital role in the shaping of government policies, including resiliency planning and disaster response. This study argues that dashboards that are action-oriented, easy-to-use, and locally embedded within the community have much more potential to be used as a decision-support system. The findings indicate that community-based knowledge networks catalyzed and influenced by modern technologies might provide a model to negotiate the gaps between ecosystem-based and social-science-focused conceptualization of community resilience.

Details

Title
BUILDING COMMUNITY RESILIENCE THROUGH GEOSPATIAL INFORMATION DASHBOARDS
Author
Praharaj, S 1   VIAFID ORCID Logo  ; Wentz, E 1 

 Knowledge Exchange for Resilience, Arizona State University, USA; Knowledge Exchange for Resilience, Arizona State University, USA 
Pages
151-157
Publication year
2022
Publication date
2022
Publisher
Copernicus GmbH
ISSN
16821750
e-ISSN
21949034
Source type
Conference Paper
Language of publication
English
ProQuest document ID
2725245906
Copyright
© 2022. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.