Proto-OKN Theme 1: A Knowledge Graph Warehouse for Neighborhood Information

  • Shang, Jingbo (CoPI)
  • Gao, Jing (PI)
  • Semenza, Daniel C. (CoPI)
  • Ma, Fenglong (CoPI)

Project: Research project

Project Details


This project aims to establish a robust and sustainable data infrastructure to integrate neighborhood-level data to assist and inform various local stakeholders. Drawing on local records, census data and other neighborhood-level data the project will construct a unified database to capture crucial connections among the variety of neighborhood-level information sources. Project outcomes include integrated neighborhood-level data and software for constructing and operating a knowledge graph warehouse. The educational component of the project will integrate outcomes from this project into course content, foster student mentoring, and promote educational innovation with a focus on inclusivity and diversity within the associated STEM programs. Working in partnership with the National Institute of Justice (NIJ) and other expert entities, this project addresses critical issues in unifying disparate data sources at the neighborhood-level, e.g., demographics, land use, local incidents and injuries, proximity to trauma centers, and the like by leveraging advanced data extraction and record linkage methods. The proposed knowledge graph warehouse is designed to organize and maintain pertinent neighborhood-level information, with data transformation achieved through zero-shot extraction techniques and key-phrase generation methods for free text data. The warehouse will support efficient querying and summarization with adaptable techniques for its unique structure, including novel pattern mining methods for trend detection, ensuring sustainability and extensibility with compatibility for other knowledge graphs, and incorporating incremental updates and extensions for new data and entity types. To ensure data accuracy, the project plans to integrate data from various local agencies, provide user feedback mechanisms, and uphold a robust metadata record. In order to mitigate biases and to provide a comprehensive view, the project will continuously update the infrastructure with new data sources, ensuring transparency through accessibility of metadata and recording of data provenance.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.
Effective start/end date10/1/239/30/26


  • National Science Foundation: $1,500,000.00


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