Designing Bias Mitigation Interventions
In this work, we explore the ways in which the design of visualizations may be used to mitigate cognitive biases. We derive a design space comprised of 8 dimensions that can be manipulated to impact a user’s cognitive and analytic processes and describe them through an example hiring scenario. This design space can be used to guide and inform future vis systems that may integrate cognitive processes more closely. We subsequently implemented one intervention, interaction traces, in the Lumos system and conducted a series of experiments to test the effectiveness.
Transformer-Based Interactive Literature Review
We developed an interactive table-based visualization for searching academic literature using a transformer-based approach. The system, VitaLITy, has an initial set of 59k articles from popular visualization venues. The open-source code can be augmented to search literature from other academic sources as well. An alternative to keyword searches, find semantically similar documents by providing a set of initial seed papers or providing a working paper title and abstract to kickstart the literature review of a new project idea.
COVID19 Health Equity Dashboard
We present a case study of the COVID-19 Health Equity Dash-board, an open-source web-based interactive data visualization that provides timely, localized, and actionable data of the ongoing COVID-19 pandemic. The dashboard features interactive maps and charts alongside population vulnerability characteristics, allowing for benchmarking county-level outcomes and disparities against the state and nation. While the dashboard faces several public health communication challenges, we continue to investigate and support data dissemination for public health officials’ decision making.
Value of Visualization
In this work, we create a heuristic-based evaluation methodology to accompany the value equation for assessing interactive visualizations. We refer to the methodology colloquially as ICE-T, based on an anagram of the four value components. Our approach breaks the four components down into guidelines, each of which is made up of a small set of low-level heuristics. Evaluators who have knowledge of visualization design principles then assess the visualization with respect to the heuristics.