Myeong Lee, Assistant Professor, Information Sciences and Technology, is working to understand how people use the 311 non-emergency issue-reporting system during the COVID-19 pandemic.
Specifically, Lee and his collaborators aim to understand how local governments support people’s different uses of the system during the COVID-19 pandemic and how the different performance metrics of local governments for 311 systems function at the metropolitan area level. During the planning grant period, the researchers are working on preparing the study with jurisdictions in the DMV area.
If this project is awarded the full grant after the planning period, the researchers will survey and consolidate local governments’ performance metrics that assess the outcomes of 311 systems in the Washington, D.C. metropolitan (DMV) area.
They will also analyze 311 datasets using artificial intelligence (AI) technologies and statistical methods to understand the changes in people’s 311 use patterns in the six jurisdictions in the DMV area during the pandemic.
From there, they will survey city officials to examine how each government has engaged the changing needs of residents.
Finally, they will build a web-based visualization tool that demonstrates the commonalities and discrepancies among local governments’ assessment metrics regarding 311 systems.
During the planning grant period, the researchers propose to achieve these goals by establishing connections with DMV’s jurisdictions through roundtables organized by a community partner, Connected DMV, and consolidating the inconsistent 311 datasets as a viable unified database.
Lee received $49,846 from the National Science Foundation for this project. This grant is a Stage-1 grant made by the Smart and Connected Communities’ Civic Innovation Challenge program, designed to empower communities to address civic needs by establishing research partnerships that can achieve not just local impacts but potentially be scaled up regionally, or even nationally. Funding began in February 2021 and will end in late July 2021.
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This part of information is sourced from https://www.eurekalert.org/pub_releases/2021-03/gmu-lc031221.php