Combatting Bias via Contextual Visualization
Research projects within this theme examine and evaluate new visual analytics methods that aim to reduce threats to validity that arise from various bias effects during exploratory visual analysis. These threats often arise from unseen effects of contextual information—such as shifts in data distributions during data selection or assumptions during cognitive activity–which are often ignored within traditional visual analytics approaches.
Publications
Using Counterfactuals to Improve Causal Inferences from Visualizations
Traditional approaches to data visualization have often focused on comparing different subsets of data, and this is reflected in the …
Human-Computer Collaboration for Visual Analytics: an Agent-based Framework
The visual analytics community has long been aiming to better understand users and assist them in their analytic endeavours. As a …
June 2023
Computer Graphics Forum (Proceedings of EuroVis 2023)
A Design Space for Surfacing Content Recommendations in Visual Analytic Platforms
Recommendation algorithms have been leveraged in various ways within visualization systems to assist users as they perform of a range …
January 2023
IEEE TVCG (Volume 29, Number 1)
Improving Visualization Interpretation Using Counterfactuals
Complex, high-dimensional data is used in a wide range of domains to explore problems and make decisions. Analysis of high-dimensional …
Risk Prediction Tools in an Intuition-Based World: A Mixed Methods Study of Urologic Surgeons
A plethora of risk prediction tools (RPTs) have been developed to support surgical decision-making. However, past studies indicate both …
Hung-Jui Tan, Allison Deal, Antonia Bennett, Susan Blalock, Alex Sox-Harris, Daniel Reuland, Arlene Chung, David Gotz, Matthew Nielsen, Ethan Basch
September 2021
American Urological Association (AUA) Annual Meeting Abstract
Modeling and Leveraging Analytic Focus During Exploratory Visual Analysis
Visual analytics systems enable highly interactive exploratory data analysis. Across a range of fields, these technologies have been …
May 2021
ACM CHI Conference on Human Factors in Computing Systems
Selection-Bias-Corrected Visualization via Dynamic Reweighting
The collection and visual analysis of large-scale data from complex systems, such as electronic health records or clickstream data, has …
Visual Analytics to Combat Selection Bias in Retrospective EHR Data Analyses
Retrospective analyses of electronic health records (EHRs) and other health data sources are increasingly common as investigators seek …
November 2020
American Medical Informatics Association (AMIA) Annual Symposium Podium Abstract
Selection Bias Tracking and Detailed Subset Comparison for High-Dimensional Data
The collection of large, complex datasets has become common across a wide variety of domains. Visual analytics tools increasingly play …
January 2020
IEEE TVCG (Volume 26, Issue 1)
Visual Analysis of High-Dimensional Event Sequence Data via Dynamic Hierarchical Aggregation
Temporal event data are collected across a broad range of domains, and a variety of visual analytics techniques have been developed to …
January 2020
IEEE TVCG (Volume 26, Issue 1)
Dynamic Hierarchical Aggregation, Selection Bias Tracking, and Detailed Subset Comparison for High-Dimensional Event Sequence Data
With the increase in collection of temporal event data, especially electronic health record (EHR) data, numerous different …
October 2019
Visual Analytics in Healthcare (VAHC) Workshop Posters
Periphery Plots for Contextualizing Heterogeneous Time-Based Data
Patterns in temporal data can often be found across different scales, such as days, weeks, and months, making effective visualization …
Visualization Model Validation via Inline Replication
Data visualizations typically show a representation of a data set with little to no focus on the repeatability or generalizability of …
January 2019
Information Visualization (Volume 18, Issue 4)
Visual Cohort Queries for High-Dimensional Data: A Design Study
The large collections of electronic health data gathered by modern health institutions are increasingly being leveraged as a source of …
November 2018
Visual Analytics in Healthcare (VAHC) Workshop
Contextual Visualization: Making the Unseen Visible to Combat Bias During Visual Analysis
Unseen information can lead to various “threats to validity” when analyzing complex datasets using visual tools, resulting in …
Dual View: Multivariate Visualization Using Linked Layouts of Objects and Dimensions
The display of multivariate data is a common task in data visualization. However as dimensionality increases, it becomes increasingly …
Increasing Understanding of Survey Re-Weighting with Visualization
Surveys are a widely used tool for inferring information about a target population by collecting data from a smaller sample. However …
Adaptive Contextualization Methods for Combating Selection Bias During High-Dimensional Visualization
Large and high-dimensional real-world datasets are being gathered across a wide range of application disciplines to enable data-driven …
November 2017
ACM TiiS (Volume 7, Issue 4)
Adaptive Contextualization: Combating Bias During High-Dimensional Visualization and Data Selection
Large and high-dimensional real-world datasets are being gathered across a wide range of application disciplines to enable data-driven …
March 2016
ACM International Conference on Intelligent User Interfaces (IUI)
Visual Assessment of Cohort Divergence During Iterative Cohort Selection
Large-scale repositories of secondary-use patient data are emerging as a critical resource for both clinical and epidemiological …