Abstract
As datasets continue to grow in size and complexity, exploring multidimensional datasets remain challenging for analysts. A common operation during this exploration is drill-downÐunderstanding the behavior of data subsets by progressively adding filters. While widely used, in the absence of careful attention towards confounding factors, drill-downs could lead to inductive fallacies. Specifically, an analyst may end up being łdeceivedž into thinking that a deviation in trend is attributable to a local change, when in fact it is a more general phenomenon; we term this the drill-down fallacy. One way to avoid falling prey to drill-down fallacies is to exhaustively explore all potential drill-down paths, which quickly becomes infeasible on complex datasets with many attributes. We present VisPilot, an accelerated visual data exploration tool that guides analysts through the key insights in a dataset, while avoiding drill-down fallacies. Our user study results show that VisPilot helps analysts discover interesting visualizations, understand attribute importance, and predict unseen visualizations better than other multidimensional data analysis baselines.
Original language | English (US) |
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Pages | 186-196 |
Number of pages | 11 |
DOIs | |
State | Published - 2019 |
Event | 24th ACM International Conference on Intelligent User Interfaces, IUI 2019 - Marina del Ray, United States Duration: Mar 17 2019 → Mar 20 2019 |
Conference
Conference | 24th ACM International Conference on Intelligent User Interfaces, IUI 2019 |
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Country/Territory | United States |
City | Marina del Ray |
Period | 3/17/19 → 3/20/19 |
Keywords
- Drill-down data analysis
- Exploratory data analysis
- Visualization recommendation
ASJC Scopus subject areas
- Software
- Human-Computer Interaction