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Building an Interdisciplinary Team for Disaster Response Research: A Data-Driven Approach.

Yue Gurt Ge1, Christopher W Zobel2, Pamela Murray-Tuite3

  • 1School of Public Administration, University of Central Florida, Orlando, FL, USA.

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Summary

Effective disaster response research requires interdisciplinary teams. This study explores three teaming models and emphasizes long-term collaboration for critical data collection and analysis in disaster research.

Keywords:
Data collectiondata-driven approachdisaster responseinterdisciplinary team

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Area of Science:

  • Disaster Science
  • Team Science
  • Interdisciplinary Research

Background:

  • Disaster response research faces challenges like acute events, limited resources, and high uncertainty.
  • Effective collaboration across disciplines is crucial for addressing complex disaster scenarios.

Purpose of the Study:

  • To examine teaming mechanisms for interdisciplinary disaster response research.
  • To identify critical data types requiring interdisciplinary collaboration.
  • To advocate for a long-term, data-driven approach to building these teams.

Main Methods:

  • Analysis of three distinct interdisciplinary teaming models: ad hoc/grant-driven, research center-based, and expertise-matched long-term collaborations.
  • Case study context using hurricane response scenarios.
  • Examination of data collection, integration, and analysis needs.

Main Results:

  • Identified three primary models for forming interdisciplinary disaster research teams.
  • Highlighted the critical role of interdisciplinary collaboration in managing diverse data types during disaster response.
  • Emphasized the need for structured, long-term research protocols.

Conclusions:

  • Recommends a strategic, long-term approach to building interdisciplinary teams for disaster response research.
  • Advocates for a data-driven methodology to guide disciplinary engagement.
  • Stresses the importance of integrated research protocols for effective disaster mitigation and recovery efforts.