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A conceptual framework and taxonomy of techniques for analyzing movement
TLDR
We present a conceptual framework that describes in a systematic and comprehensive way the possible types of information that can be extracted from movement data and on this basis defines the respective types of analytical tasks. Expand
Visual Analytics of Movement
TLDR
Visual analytics of movement data can yield exciting insights into the behavior of moving persons and objects, but can also lead to an understanding of the events that transpire when things move. Expand
Space‐in‐Time and Time‐in‐Space Self‐Organizing Maps for Exploring Spatiotemporal Patterns
TLDR
Spatiotemporal data pose serious challenges to analysts in geographic and other domains. Expand
Flowstrates: An Approach for Visual Exploration of Temporal Origin‐Destination Data
TLDR
We present Flowstrates, a new interactive visualization approach in which the origins and the destinations of the flows are displayed in two separate maps, and the changes over time of the flow magnitudes are represented in a separate heatmap view in the middle. Expand
Where Would You Go on Your Next Vacation? A Framework for Visual Exploration of Attractive Places
Tourists face a great challenge when they gather information about places they want to visit. Geographically tagged information in the form of Wikipedia pages, local tourist information pages,Expand
Generalized Scatter Plots
TLDR
We present generalized scatter plots, a generalized scatter plot technique, which allows an overlap-free representation of large data sets to fit entirely into the display. Expand
Understanding customer behavior using indoor location analysis and visualization
TLDR
We present a solution approach for better understanding customer behavior based on mobile indoor location data as well as the technologies developed by IBM Research for realizing this solution. Expand
Exploration through enrichment: a visual analytics approach for animal movement
TLDR
This paper presents an exploration through enrichment approach, which enables iterative generation of metadata based on exploratory findings and is aimed at enabling domain experts to explore their data beyond traditional means. Expand
Analysis of community-contributed space-and time-referenced data (example of Panoramio photos)
TLDR
Space- and time-referenced data published on the Web by general people can be viewed in a dual way: as independent spatio-temporal events and as trajectories of people in the geographical space. Expand
Density Equalizing Distortion of Large Geographic Point Sets
Visualizing large geo-demographical datasets using pixel-based techniques involves mapping the geospatial dimensions of a data point to screen coordinates and appropriately encoding its statisticalExpand
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