A visual analytics system for financial time-series data
Proceedings of the 3rd International Symposium on Visual Information Communication
Quantitative data visualization with interactive KDE surfaces
Proceedings of the 26th Spring Conference on Computer Graphics
A visual analytics framework for spatio-temporal analysis and modelling
Data Mining and Knowledge Discovery
Storygraph: extracting patterns from spatio-temporal data
Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics
Opening up the "black box" of medical image segmentation with statistical shape models
The Visual Computer: International Journal of Computer Graphics
Environmental Modelling & Software
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As data sources become larger and more complex, the ability to effectively explore and analyze patterns among varying sources becomes a critical bottleneck in analytic reasoning. Incoming data contain multiple variables, high signal-to-noise ratio, and a degree of uncertainty, all of which hinder exploration, hypothesis generation/exploration, and decision making. To facilitate the exploration of such data, advanced tool sets are needed that allow the user to interact with their data in a visual environment that provides direct analytic capability for finding data aberrations or hotspots. In this paper, we present a suite of tools designed to facilitate the exploration of spatiotemporal data sets. Our system allows users to search for hotspots in both space and time, combining linked views and interactive filtering to provide users with contextual information about their data and allow the user to develop and explore their hypotheses. Statistical data models and alert detection algorithms are provided to help draw user attention to critical areas. Demographic filtering can then be further applied as hypotheses generated become fine tuned. This paper demonstrates the use of such tools on multiple geospatiotemporal data sets.