CAREER: Seeing What Matters: Reframing Visualization as Data Disclosure

Visualization facilitates data communication across the sciences and society at large, yet it can be hard to know whether a visualization gives an honest depiction of evidence. One reason for this is that visualizations provide necessarily incomplete views on complex datasets. Charts that attempt to convey too much information become incomprehensible, so honest and effective visualization design requires authors to choose what information to disclose and, conversely, what aspects of data will be hidden or distorted. This project will address the problem of responsible data disclosure through visualizations. For visualization authors, it will build tools that help them balance goals such as effective communication and protecting the privacy of data subjects. For audiences, it will develop new ways to support skepticism about what a chart cannot show by design. The project will also produce novel educational materials and games to help students learn to use visualizations responsibly and avoid misinterpretations. Together, these activities will create a practical framework for understanding and espousing ethical standards for data communication. This project reframes visualization as a mechanism for data disclosure. It develops a theory defining visualization design goals in terms of balancing forms of information loss that designers and audiences care about. The theory makes these losses computable by grounding them in mathematical formalisms developed through analysis of examples, synthesis, and expert interviews. Codifying this formalism in software will enable automated reasoning over the space of possible visualization designs suited to a given goal. Indexing this design space on relevant forms of information loss will enable new ways to recommend solutions for visualization authors, as well as new interfaces that generate assistive explanations for audiences. These tools will be evaluated through software testing, user studies, and controlled experiments. To teach students about ethical data communication, and engage them in research, this project will develop data disclosure games that create opportunities to practice and reflect on responsible ways of navigating information loss with visualization. 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. NSF Award ID: 2542846 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT,01003031DB NSF RESEARCH & RELATED ACTIVIT,01002930DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Alexander Kale | Institution: University of Chicago, CHICAGO, IL | Award Amount: $402,391 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2542846 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2542846.html