The visual display of quantitative information
The visual display of quantitative information
Through the Interface: A Human Activity Approach to User Interface Design
Through the Interface: A Human Activity Approach to User Interface Design
Computational Statistics & Data Analysis - Data visualization
Exploratory Analysis of Spatial and Temporal Data: A Systematic Approach
Exploratory Analysis of Spatial and Temporal Data: A Systematic Approach
Acting with Technology: Activity Theory and Interaction Design (Acting with Technology)
Acting with Technology: Activity Theory and Interaction Design (Acting with Technology)
Coordinated Multiple Views: a Critical View
CMV '07 Proceedings of the Fifth International Conference on Coordinated and Multiple Views in Exploratory Visualization
Kaleidomaps: a new technique for the visualization of multivariate time-series data
Information Visualization
A visual analytics system for financial time-series data
Proceedings of the 3rd International Symposium on Visual Information Communication
2D and 3D representations for feature recognition in time geographical diary data
Information Visualization
Visualizing alternative scenarios of evolution in heritage architecture
i-KNOW '11 Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies
Evaluation of the visibility of vessel movement features in trajectory visualizations
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
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The timeline or track of any individual, mobile, sentient organism, whether animal or human being, represents a fundamental building block in understanding the interactions of such entities with their environment and with each other. New technologies have emerged to capture the (x, y, t) dimension of such timelines in large volumes and at relatively low cost, with various degrees of precision and with different sampling properties. This has proved a catalyst to research on data mining and visualizing such movement fields. However, a good proportion of this research can only infer, implicitly or explicitly, the activity of the individual at any point in time. This paper in contrast focuses on a data set in which activity is known. It uses this to explore ways to visualize large movement fields of individuals, using activity as the prime referential dimension for investigating space-time patterns. Visually central to the paper is the ringmap, a representation of cyclic time and activity, that is itself quasi spatial and is directly linked to a variety of visualizations of other dimensions and representations of spatio-temporal activity. Conceptuatly central is the ability to explore different levels of generalization in each of the space, time and activity dimensions, and to do this in any combination of the (s, t, a) phenomena. The fundamental tenet for this approach is that activity drives movement, and logically it is the key to comprehending pattern. The paper discusses these issues, illustrates the approach with specific example visualizations and invites critiques of the progress to date.