SCC-PG WECAN Smart Toolkit: Wellbeing Enhancement through Crowd-sourced Assessment of Neighborhood-infrastructure

This NSF Smart and Connected Community (S&CC) planning grant will design the WECAN (Wellbeing Enhancement through Crowd-sourced Assessment of Neighborhood-infrastructure) Smart Toolkit for community-driven decision making to address inequities in neighborhood infrastructure identified in previous NSF-funded research. These inequities are important because neighborhood infrastructure (e.g., sidewalks, public transit, gathering spaces, trails, etc.) provides public goods and services essential to physical, mental, social, and financial wellbeing.

The WECAN smart toolkit will couple crowd-sourced data and ideas, machine learning, social and infrastructure network analysis, agent-based modeling, and community-engaged infrastructure decision making to improve neighborhood equity and wellbeing. The planning process in this project supports in-depth and inclusive community discussions on neighborhood infrastructure needs and impacts, which will lead to better understanding of diverse perspectives and support community-driven decision making.

The focus on low-income neighborhoods with poor infrastructure, many of which are predominantly Black or Hispanic, should foster more inclusive and equitable city governance and community advocacy.

In this project, the research team and WECAN Community Task Force, with representatives from the City of Dallas, nonprofits, and for-profit entities, will advance these goals by jointly undertaking the following tasks: (1) project planning meetings to execute the project and develop a sound SCC-IRG proposal; (2) focus groups (with community development professionals and residents) and key decision-maker interviews to identify barriers to equitable neighborhood infrastructure decision making and opportunities for WECAN to overcome these barriers; and (3) WECAN Toolkit software requirements meetings. The research questions and intellectual merit are: (1) WECAN Data Discovery: How do smart multilevel social and physical infrastructure networks evolve and impact community wellbeing in neighborhoods?

A novel multilevel network approach to social and infrastructure network analysis (SINA) will be developed for predicting wellbeing. (2) WECAN Data Analytics: Can interactions among diverse social and physical infrastructure network data be better interpreted and synthesized using a novel spatiotemporal analysis called multi-modal Granger clustering, compared to traditional spatiotemporal clustering algorithms? The Granger time series clustering method will be extended to cluster spatiotemporal data based upon response to events and spatial location, rather than direct measures of similarity. (3) WECAN Toolkit Impact: How and to what extent do the WECAN tools shift equity-based infrastructure decision making?

The view of “experts” will be expanded by formally integrating opinions of community members, nonprofits, for-profits, and infrastructure users into a participatory prioritization process, as compared to existing decision-making approaches.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.