Distributed Data-Sharing for Fast Response and Decision Support
Lead PI:
N. Rich Nguyen

The vision of a smart city is underpinned by its ability to collect, manage, and use data. However, data access remains a fundamental challenge across city agencies, public institutions, and community stakeholders. This project is championing a paradigm shift in data sharing by implementing a new data access framework that allows users to share access to data in-situ instead of sending copies of data around. This project builds on the new data access paradigm to deploy a city Data Access Network (City-DAN) to support city managers get timely access to important data for fast decision and response. City-DAN is piloted first in Ho Chi Minh City, Vietnam and then scaled to other ASEAN cities. This activity is in response to NSF Dear Colleague Letter Supporting Transition of Research into Cities through the US ASEAN ((Association of Southeast Asian Nations Cities) Smart Cities Partnership in collaboration with NSF and the US State Department. The research team (University of Virginia) is working closely with stakeholders in Ho Chi Minh City including city managers, departments, and community organizers as well as Vietnam National University – International University to transition technology into practice.

The proposed distributed, peer-to-peer data access framework represents an ambitious vision of the next generation data ecosystem. This project establishes a foundational data platform to underpin smart cities by addressing issues of data integrity, provenance, control, and timely access. This project takes advantage of the unique deployment opportunity to pursue a vibrant research agenda on grid computing. Specific research areas include advanced cyber infrastructure, cybersecurity, networking, and persistent identifiers. This project will especially focus on identity and access management (IAM) in the context of unreliable infrastructure and weak level-of-assurance (identify proofing) baselines. The project will examine new approaches for enhancing reliability while balancing with transparency and QoS. Lessons learned also can be adopted to advance the smart and connected community research community in the US and other countries.

N. Rich Nguyen
Rich Nguyen is an Assistant Professor in the Department of Computer Science at the University of Virginia. His research has been dedicated to biomedical image analysis, computing education, and machine learning funded by several generous institutional and federal grants. He has authored and co-authored 20 peer-reviewed journal and conference papers in biomedical image analysis, computer vision, machine learning, and computer science education with 165+ citations on Google Scholar. He has taught machine learning courses in the Computer Science Department for seven semesters. While earning a Ph.D. in Computer Science at the University of North Carolina – Charlotte, he worked as a career manager to help students connect to over 50 companies including several from Fortune 500. Rich has also taught various courses in machine learning, introduction to algorithms, and computing professional seminars to a total of 1,458 computer science students over five years. In 2019, he was selected as a recipient of the Google Faculty Award for Machine Learning Education.
Performance Period: 07/15/2020 - 06/30/2024
Institution: University of Virginia Main Campus
Sponsor: National Science Foundation
Award Number: 2026050
Core Areas: International