Lumos: Increasing Awareness of Analytic Behavior during Visual Data Analysis

TL;DR

Lumos is a visual data analysis tool that enhances user awareness of their analytic behaviors by visualizing interaction history, thereby promoting reflection and potentially improving decision-making during data exploration.

Contribution

This paper introduces Lumos, a novel visualization system that captures and displays interaction history to increase awareness of analytic behaviors in visual data analysis.

Findings

Lumos increases user awareness of their data exploration activities.

Users reflected more on their analysis strategies with Lumos.

Lumos influenced subsequent data exploration interactions.

Abstract

Visual data analysis tools provide people with the agency and flexibility to explore data using a variety of interactive functionalities. However, this flexibility may introduce potential consequences in situations where users unknowingly overemphasize or underemphasize specific subsets of the data or attribute space they are analyzing. For example, users may overemphasize specific attributes and/or their values (e.g., Gender is always encoded on the X axis), underemphasize others (e.g., Religion is never encoded), ignore a subset of the data (e.g., older people are filtered out), etc. In response, we present Lumos, a visual data analysis tool that captures and shows the interaction history with data to increase awareness of such analytic behaviors. Using in-situ (at the place of interaction) and ex-situ (in an external view) visualization techniques, Lumos provides real-time feedback to users for them to reflect on their activities. For example, Lumos highlights datapoints that have been previously examined in the same visualization (in-situ) and also overlays them on the underlying data distribution (i.e., baseline distribution) in a separate visualization (ex-situ). Through a user study with 24 participants, we investigate how Lumos helps users' data exploration and decision-making processes. We found that Lumos increases users' awareness of visual data analysis practices in real-time, promoting reflection upon and acknowledgement of their intentions and potentially influencing subsequent interactions.