SCC-IRG: Creating a community-focused Data Management Platform
- Institution
- California State University-Long Beach Foundation, CA
- Principal investigator
- Gwen L Shaffer
- Funding
- $1.5M
- Duration
- 2025–2028
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Abstract
This multi-disciplinary project aims to promote better data governance practices and bolster trust through the development of a Data Management Platform in Long Beach, Calif. The Platform is designed to support community access to information generated by smart city technologies. The project takes a user-centric participatory design approach to the development, evaluation and refinement of a Platform designed to enable people to readily discover and learn about the data civic technologies collect about them as they engage in routine activities, such as using the bike share or passing by a traffic camera. The new Platform will enable city residents to not only discover what data is collected about them but to also limit data practices with which they are not comfortable. The resulting Data Management Platform is expected to help close the gap between the discursive and material aspects of data privacy policy. Today, dozens of U.S. cities have adopted data privacy guidelines—without being able to take practical and effective next steps to implement or enforce them. At full scale, the Data Management Platform will make data practices associated with civic technologies more obtainable for Long Beach’s nearly 500,000 residents, potentially bolstering trust in local government. The project’s methodology and technical solutions are scalable and transferable to other cities. This project centers around the design, evaluation and refinement of an IoT mobile assistant that empowers people to exercise privacy choices. Part of this research will involve developing a simple taxonomy of privacy choices and data practices that enable city residents to specify ahead of time opt-in/opt-out choices, and develop support for authenticating users and functionality. The researchers will also develop a Privacy Dashboard that can help users review what data about them might have been collected over the past day or week. Formative evaluation and user testing will inform refinements to the mobile privacy assistant and other elements of the Data Management Platform. The project’s methodology and technical solutions are scalable and transferable to cities beyond Long Beach. 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.
Research team
- Gwen L ShafferPI
- Norman M Sadeh
- Tyler D Reeb
- Ryan Kurtzman
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