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Data-Driven Decision Making in Disaster Response: Enhancing Environmental Sampling Through Data Management
Citation:
Boe, T., J. Deagan, E. Silvestri, AND S. Serre. Data-Driven Decision Making in Disaster Response: Enhancing Environmental Sampling Through Data Management. U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-23/126, 2023.
Impact/Purpose:
This technical report explores the critical role of effective data management in disaster response, particularly in the context of environmental sampling and contamination incidents. By providing a comprehensive overview of data management processes, tools, and best practices, the report showcases the application of these principles to a large-scale environmental field study, the Analysis for Coastal Operational Resiliency (AnCOR) wide area demonstration (WAD). The study aims to offer valuable insights into data acquisition, management, and visualization strategies, addressing the growing challenges of big data in disaster response and recovery. Through the examination of the AnCOR WAD, the report emphasizes the need for accurate, accessible, and organized data, as well as effective Data Management Plans (DMPs), to facilitate informed decision-making, coordination, and cleanup efforts.
Description:
This report highlights the importance of effective data management in disaster response, specifically focusing on environmental sampling. In today's data-driven world, data management is crucial for decision-making, coordination, and systems thinking in disaster scenarios. Efficiently managing data allows organizations to enhance decision-making and optimize operations, which is especially vital in incidents involving contaminants posing risks to human health and the environment. This report aims to provide an in-depth understanding of data management and visualization strategies used during the Analysis for Coastal Operational Resiliency (AnCOR) Wide Area Demo (WAD), discussing the roles, processes, technologies, tools, and software used, as well as the outcomes and lessons learned from the AnCOR WAD. The report is organized into three main sections: Methodology, Case Study, and Discussion. The Methodology section provides an overview of data management processes, which include organizing, storing, validating, and maintaining data throughout its lifecycle. The Case Study section demonstrates the application of these principles to the AnCOR WAD, describing the tools and software used to support planning and decision-making processes. The Discussion section reflects on the challenges faced, the solutions devised, and the knowledge gained throughout the project's lifecycle, focusing on data management best practices. By applying the principles outlined in the report to a large-scale environmental field study, the effectiveness of data management practices and tools can be showcased. This comprehensive overview of data management in disaster response, with an emphasis on environmental sampling, aims to address the growing challenges in management of large datasets in disaster response and recovery, especially in contamination incidents. The report emphasizes the need for accurate, accessible, and organized data, as well as effective Data Management Plans (DMPs), to facilitate characterization and cleanup efforts.