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Danielle Szafir presented “Making Data Visible: Cognitively-Driven Data Visualization @ The VisuaLab,” which provided an overview of projects at The VisuaLab, comprised of researchers working to make data analysis more efficient by studying, understanding, and predicting how people will work with and interpret data. Sfazir shared an example of the group’s approach to build models of how people make sense of data, and use those models to drive new techniques for visualizing and representing data. Szafir explained that the models use techniques from the areas of psychology and cognition to understand what goes through someone’s mind when they are looking at data, which in turn inspires tools that can be used for analysis. One tool involved integrating models for how best to use color in visualization models and allows the researcher to adjust the colors to make them as effective as possible in the visualization. Sfazir also shared a project called Scholastic, a machine learning tool that aims to identify patterns that researchers are using as they annotated their own data and eventually become a collaborator led by the research team. She highlighted the importance of developing accessible systems that enable people to accurately explore data at scale, regardless of marginalization, ability, and age. Finally, Sfazir shared projects that focus on bringing data into the real world, and leverage technologies such as augmented reality, virtual reality, and 3D printing to integrate context into data analysis. These projects aim to provide real-time insights to researchers monitoring collection inputs and data quality. Click here to view the talk on YouTube.


Danielle Szafir, Assistant Professor

Department: Computer Science | Faculty Profile

Featured on: June 23, 2022 (Event Page)

Session Title: Data Science: More than Numbers (Event Recap

Tools, Information, and Resources:

  • VisuaLab: VisuaLab explores the intersection of data science, visual cognition, and computer graphics. Our goal is to understand how people make sense of visual information to create better interfaces for exploring and understanding information. We work with scholars from psychology to biology to the humanities to design and implement visualization systems that help drive innovation. Our ultimate mission is to facilitate the dialog between people and technologies that leads to discovery.
  • Danielle Szafir’s Research Site