Project Grant 2340539

Award Date 6/1/24
Completion Date 5/31/29
Dollars Obligated $249K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Atlanta, GA 30322, USA
Similar Awards
The National Science Foundation (NSF) awarded Emory University a $683,097 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant, titled "Collaborative Research: HCC: Medium: Modeling and Mitigating Confirmation Bias in Visual Data Analysis", runs from November 1, 2023 to October 31, 2027. The project aims to investigate confirmation bias in data analysis and develop interventions to help data analysts make less biased decisions. Key...
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 $632,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to enable computers to serve as more reliable and robust assistants in providing guidance and feedback to help analysts make effective data visualization design decisions. The key objectives are to develop "provably effective" visualization analyses that can be tested against best practices and theoretical models,...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) provides $316,000 to the University of Utah to conduct research towards enabling computers to serve as more reliable and robust assistants that provide guidance and feedback to help analysts make effective data visualization design decisions. The key objectives are to develop "provably effective" visualization analyses that can be tested against best...
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...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program grant, awarded to Carnegie Mellon University, aims to provide a systematic framework for visualizing, understanding, and rewriting the learned computations of multimodal generative models. The $400,000 award will focus on three key research thrusts: 1) developing new methodologies to visualize the internal mechanisms and hierarchical structures of pre-trained multimodal generative models, 2)...
This $325,000 Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports research at the University of Chicago to investigate the role of different memory systems in guiding decision-making for novel choices. The research team plans to leverage eye-tracking, functional magnetic resonance imaging (fMRI), computational modeling, and patient populations to characterize how "rigid" and "flexible"...
This $250,000 Project Grant awarded by the National Science Foundation (NSF) under its Computer and Information Science and Engineering (CFDA 47.070) program will support research to improve public decision-making through the development of statistical methods to understand biases in crowdsourced data. The project, titled "CAREER: Public Decision-Making with Crowdsourced Data", aims to: Measure biases in public crowdsourcing of incident reports and community health monitoring data,...
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 Project Grant award for $540,000 from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports a collaborative research project at Northeastern University focused on developing responsive uncertainty visualizations to improve human-centered decision-making. The project aims to create methods for modeling people's abilities and needs, and to develop a library of uncertainty representation approaches that can be combined...

CAREER: PROMOTING METACOGNITION IN VISUAL ANALYTICS -DATA-DRIVEN DECISION-MAKING REQUIRES THE PEOPLE ENGAGED IN IT TO MAKE A NUMBER OF CHOICES ABOUT THE DATA TO COLLECT, AND THE METHODS FOR COLLECTING IT AND ANALYZING IT, AS WELL AS THE INTERPRETATION OF THE RESULTS. COGNITIVE, CULTURAL, AND DATA BIASES CAN INTERFERE WITH THESE PROCESSES AT EVERY STAGE, REQUIRING DATA ANALYSTS TO BE THOUGHTFUL AND REFLECTIVE AS THEY DO THEIR WORK. THIS PROJECT?S GOAL IS TO HELP ANALYSTS REDUCE THEIR BIASES THROUGH TOOLS THAT HELP THEM CRITICALLY ASSESS THEIR THOUGHT PROCESSES USING METACOGNITION, OR THINKING ABOUT THINKING. METACOGNITION WILL BE A GUIDING IDEA FOR DEVELOPING TOOL FEATURES THAT HELP ANALYSTS BE AWARE OF POSSIBLE BIASES. STUDIES OF METACOGNITION HAVE SHOWN THAT IT CAN BE HELPFUL IN OTHER EDUCATIONAL AND ANALYSIS SETTINGS; THIS PROJECT WILL USE IDEAS FROM THOSE STUDIES TO DEVELOP METHODS THAT IDENTIFY POTENTIAL BIASES AND PRESENT ACTIVITIES TO HELP ANALYSTS AVOID THEM. THE PROJECT TEAM WILL ALSO CREATE EDUCATIONAL MATERIALS AND WORK WITH NON-PROFIT PARTNER ORGANIZATIONS TO HELP THE GENERAL PUBLIC THINK MORE DEEPLY ABOUT THEIR OWN ANALYTIC STRATEGIES AND HOW THEY MIGHT BE IMPROVED. THIS PROJECT WILL APPLY THEORIES OF METACOGNITION TO ADDRESS HUMAN BIASES AND IMPROVE DECISION-MAKING PROCESSES ON AN INDIVIDUAL LEVEL. THE PROJECT IS STRUCTURED AROUND FOUR RESEARCH THRUSTS. THE RESEARCHERS WILL FIRST ORGANIZE THEORIES OF METACOGNITION AND TRANSLATE THEM INTO AN ACTIONABLE DESIGN SPACE OF METACOGNITIVE INTERVENTIONS IN VISUAL ANALYTICS (THRUST I). NEXT, THE RESEARCHERS WILL WORK ALONGSIDE NON-PROFIT PARTNER ORGANIZATIONS TO CO-DESIGN AND DEVELOP A SUITE OF METACOGNITIVE INTERVENTIONS (THRUST II) AND EVALUATE THOSE INTERVENTIONS IN A SERIES OF LABORATORY EXPERIMENTS (THRUST III). FINALLY, THE RESEARCHERS WILL ASSESS THE EXTENT TO WHICH EMPIRICAL FINDINGS TRANSLATE TO REAL-WORLD EFFICACY IN A CASE STUDY DEPLOYMENT OF METACOGNITIVE INTERVENTIONS (THRUST IV). THIS WORK WILL TEST WHETHER META-COGNITIVE INTERVENTIONS, WHEN SUCCESSFULLY APPLIED IN DATA-DRIVEN DECISION-MAKING, CAN BOTH BOOST AWARENESS OF THE TECHNICAL ACCURACY OF ANALYTIC RESULTS AND FOSTER MORE THOUGHTFUL, SOCIALLY ACCOUNTABLE, AND DILIGENT PRACTICES IN DATA ANALYSIS. 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.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

Posted 2/14/24, 12:00 AM