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Visualized data often have dubious origins and quality. Diierent forms of uncertainty and errors are also introduced as the data are derived, transformed, interpolated, and nally rendered. In the absence of integrated presentation of data and uncertainty, the analysis of the visualization is incomplete at best and often leads to inaccurate or incorrect(More)
From the standpoint of supporting human-centered discovery of knowledge, the present-day model of mining association rules suuers from the following serious shortcomings: (i) lack of user exploration and control, (ii) lack of focus, and (iii) rigid notion of relationships. In eeect, this model functions as a black-box, admitting little user interaction in(More)
This paper focuses on how computer graphics and visualization can help users access and understand the increasing volume of geo-spatial data. In particular, this paper highlights some of the visualization challenges in visualizing uncertainty associated with geo-spatial data. Uncertainty comes in a variety of forms and representations, and require different(More)
From the standpoint of supporting human-centered discovery of knowledge, the present-day model of mining association rules suffers from the following serious shortcomings: (i) lack of user exploration and control, (ii) lack of focus, and (iii) rigid notion of relationships. In effect, this model functions as a black-box, admitting little user interaction in(More)
This paper presents a seed placement strategy for streamlines based on flow features in the dataset. The primary goal of our seeding strategy is to capture flow patterns in the vicinity of critical points in the flow field, even as the density of streamlines is reduced. Secondary goals are to place streamlines such that there is sufficient coverage in(More)
Uncertainty or errors are introduced in fluid flow data as the data is acquired, transformed and rendered. Although researchers are aware of these uncertainties, little has been done to incorporate them in the existing visualization systems for fluid flow. In the absence of integrated presentation of data and its associated uncertainty , the analysis of the(More)
Visualization of 3D tensor fields continues to be a major challenge in terms of providing intuitive and uncluttered images that allow the users to better understand their data. The primary focus of this paper is on finding a formulation that lends itself to a stable numerical algorithm for extracting stable and persistent topological features from 2nd order(More)
Increasingly, more importance is placed on the uncertainty information of data being displayed. This paper focuses on techniques for visualizing 3D scalar data sets with corresponding uncertainty information at each point which is also represented as a scalar value. In Djurcilov (in: we presented two general methods (inline DVR approach and a(More)