Project Grant 2211845

Award Date 10/1/22
Completion Date 9/30/26
Dollars Obligated $1.2M
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Chapel Hill, NC 27599, USA
Similar Awards
This $343,324 National Science Foundation project grant supports research at Northeastern University to develop empirically validated perceptual tasks for data visualization. The goal is to refine and evaluate a model of the lower-level perceptual processes underlying higher-level data analysis and visualization tasks. Researchers will conduct qualitative studies to document how people decompose tasks and then empirically evaluate proposed perceptual subtasks like filtering images, judging...
The National Science Foundation awarded a $550,000 project grant to Arizona State University under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) for the period of October 1, 2022 through September 30, 2025. The grant will support the development of novel techniques and open source software tools to enable the creation of privacy-preserving data visualizations. A visualization grammar will be established to specify visualization designs that consider...
The National Science Foundation (NSF) awarded a $599,518 Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070) to the University of Maryland, College Park. This five-year grant, which began on September 1, 2023, will support research into "Manipulable Semantic Components in Data Visualization Design." The key focus of the project is to develop new interaction paradigms for data visualization design, enabling flexible manipulation of graphical...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $632,000 to the University of Washington to develop advanced techniques for enabling computers to provide more effective guidance and feedback for data visualization design. The key objectives are to create "provably effective" visualization analysis methods that can be automated and integrated into visualization tools, helping...
This $187,194 Project Grant award, funded by the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program, supports a research study on how effectively data visualizations communicate scientific information to the general public. The researchers at the National Opinion Research Center (NORC) will conduct an online survey of 2,000 U.S. adults to evaluate their understanding and interpretation of different data visualization designs, such as bar and...
This three-year, $350,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop a knowledge platform and related tools to bridge the gap between visualization research and design practice. Specifically, the Trustees of Boston College will receive funding to build a comprehensive online framework for improving access to and learning about effective visualization design principles. This framework will consolidate existing...
This Project Grant award, valued at $540,000.00, was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports a collaborative research project between researchers at Northeastern University to develop methods for designing "responsive uncertainty visualizations" that can effectively communicate the uncertainty in data to users with varying levels of expertise and decision-making needs. The...
This National Science Foundation (NSF) Social, Behavioral, and Economic Sciences (SBE) Program (CFDA 47.075) Project Grant award to Iowa State University of Science and Technology provides $305,912 from August 1, 2024 to July 31, 2027 to examine how accurately U.S. adults interpret different types of data visualizations. The researchers will implement an online survey of 2,000 respondents to measure their understanding and interpretation of various data visualization designs, such as bar and...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award of $316,000 to the University of Utah aims to enable computers to serve as more reliable and robust assistants in guiding analysts to make effective data visualization design decisions. The project targets three interleaved technical challenges: modeling user goals and knowledge to reason about visualization strategies, developing richer specification-level...
This $462,500 Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering program (CFDA 47.070), supports the development of advanced causal inference methods for data-driven decision making. Key products and services to be delivered include: Automated and robust causal AI systems that integrate machine learning and causal inference techniques to enable more decision-makers to leverage causal analysis. The project will...

This Project Grant from the National Science Foundation's Computer and Information Science and Engineering program provides $1.2 million to the University of North Carolina at Chapel Hill to develop counterfactual-centered methods for data visualization from October 1, 2022 to September 30, 2026. The university will design and implement new computational techniques and open-source software to enhance traditional data visualization tools. By incorporating comparisons to counterfactual data subsets, the methods aim to help users make more robust conclusions and reduce errors when inferring causal relationships from visualized patterns. The software will guide exploratory analysis using statistics derived from counterfactual data to increase efficiency of pattern discovery. Additionally, the project will account for secondary variables correlated with those used for counterfactual comparisons. The results are intended to improve the accuracy of inferences drawn from data visualization across different application domains, including potential benefits for population health.

Generated 1/7/24, 12:13 PM