Abstract
This article describes the research agenda for the Visual Analytics and Data Exploration Research (VADER) Lab at Arizona State University. Over the past decade, the VADER Lab has focused on creating novel algorithms, tools and visualizations for spatiotemporal data. This article will highlight past success in spatiotemporal analysis, explainable AI, graph mining, and mathematical topology. While, at first, these topics seem largely disjoint, we will describe how the underpinnings of spatiotemporal analysis has informed the various research directions in the VADER Lab, and how this research agenda has served to form a network of strong international collaborations. Finally, we will outline a vision for the Lab's future research.
Original language | English (US) |
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Pages (from-to) | 14-22 |
Number of pages | 9 |
Journal | Visual Informatics |
Volume | 5 |
Issue number | 1 |
DOIs | |
State | Published - Mar 2021 |
Keywords
- Explainable AI
- Spatiotemporal
- Topology
- Visualization
ASJC Scopus subject areas
- Software
- Human-Computer Interaction
- Computer Graphics and Computer-Aided Design