A Data-Driven Approach for Decision Making in a Regional Interdisciplinary Resiliency Center
Thinesh Selvaratnam , Rinaz Riyaz Mohamed , Berna Eren-Tokgoz , Liv Haselbach , Ginger Gummelt , Brian D. Williams , Matthew I. Pyne
International Journal of Disaster Risk Science ›› 2025, Vol. 16 ›› Issue (3) : 513 -520.
A Data-Driven Approach for Decision Making in a Regional Interdisciplinary Resiliency Center
Lamar University established a Center for Resiliency in 2021 in response to the increasing natural and human-made disasters in the Southeast Texas region. Now more than ever a robust decision-making framework is essential for this recently established regional interdisciplinary resiliency center to make well-informed decisions, prioritize funding effectively, and nurture collaboration across various fields to help communities vulnerable to these threats. This article provides a progress update and presents a methodology integrating VOSviewer and Google Trends to develop such a decision-making framework for the Center for Resiliency at Lamar University in the Southeast Texas region. Four prominent study areas in resilience—Climate Stressors and Disasters, Mental Wellness, Energy and Optimization, and Resilience Planning—were identified. These findings were validated with real-time insights from Google Trends, ensuring practical relevance to recent resilience needs to provide an understanding of evolving resilience dynamics. Furthermore, the paper discusses the status of research conducted at the Lamar University Center for Resiliency, showcasing its commitment to fostering resilience through diverse initiatives across five academic colleges. Integrating VOSviewer and Google Trends offers a robust framework for informed decision making, aligning research efforts with the Southeast Texas region’s current and future resilience needs.
Decision making / Disaster decision making / Google trends / Resiliency center / Resilience science / VOSviewer
| [1] |
American Society of Civil Engineers. 2022. Reliability and resilience in the balance. https://www.texasce.org/our-programs/beyond-storms/. Accessed 26 May 2025. |
| [2] |
|
| [3] |
Blake, E.S., and D.A. Zelinsky. 2018. Hurricane Harvey 17 August–1 September 2017. Miami, FL: National Weather Service NOAA. https://www.nhc.noaa.gov/dat0061/tcr/AL092017_Harvey.pdf. Accessed 26 May 2025. |
| [4] |
|
| [5] |
Chris, M. 2018. Hurricane Harvey was year’s costliest U.S. disaster at $125 billion in damages. https://www.texastribune.org/2018/01/08/hurricane-harvey-was-years-costliest-us-disaster-125-billion-damages/. Accessed 26 May 2025. |
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
|
| [10] |
|
| [11] |
|
| [12] |
|
| [13] |
|
| [14] |
National Oceanic and Atmospheric Administration. 2022. Hurricane costs. https://coast.noaa.gov/states/fast-facts/hurricane-costs.html. Accessed 26 May 2025. |
| [15] |
|
| [16] |
|
| [17] |
U.S. Army Corps of Engineers. 2017. Principal port of the United States. https://usace.contentdm.oclc.org/digital/collection/p16021coll2/id/3114. Accessed 17 Apr 2024. |
| [18] |
|
| [19] |
|
| [20] |
Wang, C., T. Lv, and X. Deng. 2020. Bibliometric and visualized analysis of China’s smart grid research 2008–2018. Frontiers in Research Metrics and Analytics 5. https://doi.org/10.3389/frma.2020.551147. |
| [21] |
|
The Author(s)
/
| 〈 |
|
〉 |