My prior research experience focused on evaluating information visualizations and designing patient-friendly personal diagnostic reports.
Quantifying Value of a Visualization
Even though visualizations and visualization systems are increasingly being used for decision making, it is difficult to evaluate and measure their utility. One approach available to visualization and analytics communities, is to deploy a visualization or system in production and observe its usage over time like in MILC (Multi-dimensional In-Depth Long term Case studies). However, undertaking such a study requires time and can be logistically challenging.
In this project, funded by the US Department of Energy through Sandia National Labs, I worked with a team comprising Dr. Emily Wall, Dr. Laura Matzen, Dr. Kristin Divis, Michael Haass, Dr. Alex Endert, and Dr. John Stasko. We developed and tested a low cost heuristic-based evaluation methodology that provides a method to measure the value of one or more visualizations along 4 dimensions- Insights it spurs, Confidence about the data and domain it inspires, overall Essence of data it conveys and Time it helps saves (ICE-T).
A heuristic approach to value-driven evaluation of visualizations. IEEE transactions on visualization and computer graphics, 25(1), 491-500. Wall, E., Agnihotri, M., Matzen, L., Divis, K., Haass, M., Endert, A., & Stasko, J. (2018).
Evaluating Discoverability of Tablet Visualization Systems
While a number of tablet visualization systems exist in the research community, very few visualization/BI systems exist in production and accessible to users. One possible reason for this is the complexity of the features in BI systems and how supporting the same functionalities on a tablet system requires introducing unfamiliar interaction mechanisms to the user. If parts of the interface are not easily discoverable to users, it affects the learnability and usability of the system which could affect adoption.
In this project, I assisted Dr. Ramik Sadana and Dr. John Stasko in evaluating the discoverability of a tablet visualization system- Tangere and compared it to a commercially available tablet viz system- Tableau’s Vizable.
Designing Patient Friendly Personal Diagnostic System
While patients increasingly have access to their clinical reports, they typically lack the medical training required to comprehend and contextualize the information present in their diagnostic reports. In this project, I either worked in a team or independently to answer the following research questions- what are the information needs of cancer patients from their radiology reports? What specific kinds of information do patients look for while browsing and comparing their diagnostic history? What challenges do they face during those activities and what visual and interaction techniques can we design to aid those activities? I worked with Dr. Matthew Hong, Clayton Feustel, Max Silverman, Dr. Stephen Simoneaux and Dr. Lauren Wilcox on these projects.
“Supporting families in reviewing and communicating about radiology imaging studies.” In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, pp. 5245-5256. 2017. Hong, Matthew K., Clayton Feustel, Meeshu Agnihotri, Max Silverman, Stephen F. Simoneaux, and Lauren Wilcox.