Results 1 - 10
of
90
Force-Directed Edge Bundling for Graph Visualization
, 2009
"... Graphs depicted as node-link diagrams are widely used to show relationships between entities. However, nodelink diagrams comprised of a large number of nodes and edges often suffer from visual clutter. The use of edge bundling remedies this and reveals high-level edge patterns. Previous methods requ ..."
Abstract
-
Cited by 81 (1 self)
- Add to MetaCart
Graphs depicted as node-link diagrams are widely used to show relationships between entities. However, nodelink diagrams comprised of a large number of nodes and edges often suffer from visual clutter. The use of edge bundling remedies this and reveals high-level edge patterns. Previous methods require the graph to contain a hierarchy for this, or they construct a control mesh to guide the edge bundling process, which often results in bundles that show considerable variation in curvature along the overall bundle direction. We present a new edge bundling method that uses a self-organizing approach to bundling in which edges are modeled as flexible springs that can attract each other. In contrast to previous methods, no hierarchy is used and no control mesh. The resulting bundled graphs show significant clutter reduction and clearly visible high-level edge patterns. Curvature variation is furthermore minimized, resulting in smooth bundles that are easy to follow. Finally, we present a rendering technique that can be used to emphasize the bundling.
Geometry-Based edge clustering for graph visualization
- IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
, 2008
"... Graphs have been widely used to model relationships among data. For large graphs, excessive edge crossings make the display visually cluttered and thus difficult to explore. In this paper, we propose a novel geometry-based edge-clustering framework that can group edges into bundles to reduce the ove ..."
Abstract
-
Cited by 60 (4 self)
- Add to MetaCart
(Show Context)
Graphs have been widely used to model relationships among data. For large graphs, excessive edge crossings make the display visually cluttered and thus difficult to explore. In this paper, we propose a novel geometry-based edge-clustering framework that can group edges into bundles to reduce the overall edge crossings. Our method uses a control mesh to guide the edge-clustering process; edge bundles can be formed by forcing all edges to pass through some control points on the mesh. The control mesh can be generated at different levels of detail either manually or automatically based on underlying graph patterns. Users can further interact with the edge-clustering results through several advanced visualization techniques such as color and opacity enhancement. Compared with other edge-clustering methods, our approach is intuitive, flexible, and efficient. The experiments on some large graphs demonstrate the effectiveness of our method.
Hierarchical aggregation for information visualization: Overview, techniques, and design guidelines
- IEEE Transactions on Visualization and Computer Graphics
"... Abstract—We present a model for building, visualizing, and interacting with multiscale representations of information visualization techniques using hierarchical aggregation. The motivation for this work is to make visual representations more visually scalable and less cluttered. The model allows fo ..."
Abstract
-
Cited by 57 (1 self)
- Add to MetaCart
(Show Context)
Abstract—We present a model for building, visualizing, and interacting with multiscale representations of information visualization techniques using hierarchical aggregation. The motivation for this work is to make visual representations more visually scalable and less cluttered. The model allows for augmenting existing techniques with multiscale functionality, as well as for designing new visualization and interaction techniques that conform to this new class of visual representations. We give some examples of how to use the model for standard information visualization techniques such as scatterplots, parallel coordinates, and node-link diagrams, and discuss existing techniques that are based on hierarchical aggregation. This yields a set of design guidelines for aggregated visualizations. We also present a basic vocabulary of interaction techniques suitable for navigating these multiscale visualizations. Index Terms—Aggregation, clustering, clutter reduction, massive datasets, visual exploration, visual analytics. 1
Understanding and Characterizing Insights: How Do People Gain Insights Using Information Visualization?
"... Even though “providing insight ” has been considered one of the main purposes of information visualization (InfoVis), we feel that insight is still a not-well-understood concept in this context. Inspired by research in sensemaking, we realized the importance of the procedural aspects in understandin ..."
Abstract
-
Cited by 33 (1 self)
- Add to MetaCart
(Show Context)
Even though “providing insight ” has been considered one of the main purposes of information visualization (InfoVis), we feel that insight is still a not-well-understood concept in this context. Inspired by research in sensemaking, we realized the importance of the procedural aspects in understanding insight. Thus, rather than asking “What is insight? ” we instead focus on “How do people gain insights? ” In an effort to better understand and characterize insight, we reviewed previous literature in InfoVis, seeking other researchers ’ comments and views on this concept. We found that: 1) Insights are often regarded as end results of using InfoVis and the procedures to gain insight have been largely veiled; 2) Four largely distinctive processes of gaining insight (Provide Overview, Adjust, Detect Pattern, and Match Mental Model) have been discussed in the InfoVis literature; and 3) These different processes provide some hints to understand the procedures in which insight can be gained from InfoVis. We hope that our findings help researchers and practitioners evaluate InfoVis systems and technologies in a more insight-oriented way. Categories and Subject Descriptors
Visual clustering in parallel coordinates
- COMPUTER GRAPHICS FORUM
, 2008
"... Parallel coordinates have been widely applied to visualize high-dimensional and multivariate data, discerning patterns within the data through visual clustering. However, the effectiveness of this technique on large data is reduced by edge clutter. In this paper, we present a novel framework to redu ..."
Abstract
-
Cited by 31 (6 self)
- Add to MetaCart
(Show Context)
Parallel coordinates have been widely applied to visualize high-dimensional and multivariate data, discerning patterns within the data through visual clustering. However, the effectiveness of this technique on large data is reduced by edge clutter. In this paper, we present a novel framework to reduce edge clutter, consequently improving the effectiveness of visual clustering. We exploit curved edges and optimize the arrangement of these curved edges by minimizing their curvature and maximizing the parallelism of adjacent edges. The overall visual clustering is improved by adjusting the shape of the edges while keeping their relative order. The experiments on several representative datasets demonstrate the effectiveness of our approach.
Quality metrics in high-dimensional data visualization: an overview and systematization
- IEEE TRANS. ON VISUALIZATION AND COMPUTER GRAPHICS
, 2011
"... In this paper, we present a systematization of techniques that use quality metrics to help in the visual exploration of meaningful patterns in high-dimensional data. In a number of recent papers, different quality metrics are proposed to automate the demanding search through large spaces of alterna ..."
Abstract
-
Cited by 29 (4 self)
- Add to MetaCart
(Show Context)
In this paper, we present a systematization of techniques that use quality metrics to help in the visual exploration of meaningful patterns in high-dimensional data. In a number of recent papers, different quality metrics are proposed to automate the demanding search through large spaces of alternative visualizations (e.g., alternative projections or ordering), allowing the user to concentrate on the most promising visualizations suggested by the quality metrics. Over the last decade, this approach has witnessed a remarkable development but few reflections exist on how these methods are related to each other and how the approach can be developed further. For this purpose, we provide an overview of approaches that use quality metrics in high-dimensional data visualization and propose a systematization based on a thorough literature review. We carefully analyze the papers and derive a set of factors for discriminating the quality metrics, visualization techniques, and the process itself. The process is described through a reworked version of the well-known information visualization pipeline. We demonstrate the usefulness of our model by applying it to several existing approaches that use quality metrics, and we provide reflections on implications of our model for future research.
How Information Visualization Novices Construct Visualizations
, 2010
"... It remains challenging for information visualization novices to rapidly construct visualizations during exploratory data analysis. We conducted an exploratory laboratory study in which information visualization novices explored fictitious sales data by communicating visualization specifications to a ..."
Abstract
-
Cited by 28 (4 self)
- Add to MetaCart
(Show Context)
It remains challenging for information visualization novices to rapidly construct visualizations during exploratory data analysis. We conducted an exploratory laboratory study in which information visualization novices explored fictitious sales data by communicating visualization specifications to a human mediator, who rapidly constructed the visualizations using commercial visualization software. We found that three activities were central to the iterative visualization construction process: data attribute selection, visual template selection, and visual mapping specification. The major barriers faced by the participants were translating questions into data attributes, designing visual mappings, and interpreting the visualizations. Partial specification was common, and the participants used simple heuristics and preferred visualizations they were already familiar with, such as bar, line and pie charts. From our observations, we derived abstract models that describe barriers in the data exploration process and uncovered how information visualization novices think about visualization specifications. Our findings support the need for tools that suggest potential visualizations and support iterative refinement, that provide explanations and help with learning, and that are tightly integrated into tool support for the overall visual analytics process.
Skeleton-based edge bundling for graph visualization
- IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2011, 17 (12), PP 2364-2373
, 2011
"... ..."
(Show Context)
Winding roads: Routing edges into bundles
, 2010
"... Visualizing graphs containing many nodes and edges efficiently is quite challenging. Drawings of such graphs generally suffer from visual clutter induced by the large amount of edges and their crossings. Consequently, it is difficult toreadtherelationshipsbetweennodesandthe high-level edgepatternsth ..."
Abstract
-
Cited by 22 (2 self)
- Add to MetaCart
(Show Context)
Visualizing graphs containing many nodes and edges efficiently is quite challenging. Drawings of such graphs generally suffer from visual clutter induced by the large amount of edges and their crossings. Consequently, it is difficult toreadtherelationshipsbetweennodesandthe high-level edgepatternsthatmayexistinstandard node link diagram representations. Edge bundling techniques have been proposed to help solve this issue, which rely on high quality edge rerouting. In this paper, we introduce an intuitive edge bundling technique which efficiently reduces edge clutter in graphs drawings. Our method is based on the use of a grid built using the original graph to compute the edge rerouting. In comparison with previously proposed edge bundling methods, our technique improves both the level of clutter reduction and the computation performance. The second contribution of this paper is a GPU-based rendering method which helps users perceive bundles densities while preserving edge color.
Whisper: Tracing the spatiotemporal process of information diffusion in real time
- TVCG
, 2012
"... Fig. 1. The figure shows a diffusion of information on Twitter regarding a recent 6.8 magnitude earthquake and a series of aftershocks and tsunamis that hit the northern coast of Hokkaido island (a demo on youtube: ..."
Abstract
-
Cited by 19 (7 self)
- Add to MetaCart
(Show Context)
Fig. 1. The figure shows a diffusion of information on Twitter regarding a recent 6.8 magnitude earthquake and a series of aftershocks and tsunamis that hit the northern coast of Hokkaido island (a demo on youtube:
