Generalizing Geometric Graphs

Brunel, Edith; Gemsa, Andreas; Krug, Markus; Rutter, Ignaz; Wagner, Dorothea

doi:10.1007/978-3-642-25878-7_18

Cited by 6 publications

(4 citation statements)

References 29 publications

(24 reference statements)

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“…Figure 1(e) illustrates an example of edge bundling. Other forms of clutter reduction approaches include node aggregation (Wattenberg, 2006;Dunne and Shneiderman, 2013;Zinsmaier et al, 2012), topology compression (Shi et al, 2013;Brunel et al, 2014), and sampling algorithms (Gao et al, 2014). This paper focuses on GraphMaps, proposed by Nachmanson et al (Nachmanson et al, 2015), that reduces clutter by distributing nodes to different zoom levels and routing edges on shared rails.…”

Section: Related Workmentioning

confidence: 99%

A New Approach to GraphMaps, a System Browsing Large Graphs as Interactive Maps

Mondal

Nachmanson

2018

Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Application

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A GraphMaps is a system that visualizes a graph using zoom levels, which is similar to a geographic map visualization. GraphMaps reveals the structural properties of the graph and enables users to explore the graph in a natural way by using the standard zoom and pan operations. The available implementation of GraphMaps faces many challenges such as the number of zoom levels may be large, nodes may be unevenly distributed to different levels, shared edges may create ambiguity due to the selection of multiple nodes. In this paper, we develop an algorithmic framework to construct GraphMaps from any given mesh (generated from a 2D point set), and for any given number of zoom levels. We demonstrate our approach introducing competition mesh, which is simple to construct, has a low dilation and high angular resolution. We present an algorithm for assigning nodes to zoom levels that minimizes the change in the number of nodes on visible on the screen while the user zooms in and out between the levels. We think that keeping this change small facilitates smooth browsing of the graph. We also propose new node selection techniques to cope with some of the challenges of the GraphMaps approach.

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Section: Related Workmentioning

confidence: 99%

A New Approach to GraphMaps, a System Browsing Large Graphs as Interactive Maps

Mondal

Nachmanson

2018

Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Application

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“…One of the most popular is edge bundling, which deforms and groups together edges that are similar according to some metric (see [32] for a survey). Another approach, called geometric graph generalization, reduces vertex and/or edge clutter by collapsing groups of vertices that are geometrically close to one another into a single point [7]. Differently from our stratification, edge bundling and geometric graph generalization modify the input drawing, emphasizing its skeletal structure at the expenses of loss of details.…”

Section: Related Workmentioning

confidence: 99%

Exploring Complex Drawings via Edge Stratification

et al. 2013

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Abstract. We propose an approach that allows a user to explore a layout produced by any graph drawing algorithm, in order to reduce the visual complexity and clarify its presentation. Our approach is based on stratifying the drawing into layers with desired properties; layers can be explored and combined by the user to gradually acquire details. We present stratification heuristics, a user study, and an experimental analysis that evaluates how our stratification heuristics behave on the drawings computed by a variety of popular force-directed algorithms.

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“…Aggregation techniques group vertices and edges of the graph together to obtain a smaller graph [10]. Most techniques compute a hierarchical partitioning and offer interaction to explore different branches of the tree.…”

Section: Introductionmentioning

confidence: 99%

GraphMaps: Browsing Large Graphs as Interactive Maps

Nachmanson

Prutkin

Lee

et al. 2015

Lecture Notes in Computer Science

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Algorithms for laying out large graphs have seen significant progress in the past decade. However, browsing large graphs remains a challenge. Rendering thousands of graphical elements at once often results in a cluttered image, and navigating these elements naively can cause disorientation. To address this challenge we propose a method called GraphMaps, mimicking the browsing experience of online geographic maps. GraphMaps creates a sequence of layers, where each layer refines the previous one. During graph browsing, GraphMaps chooses the layer corresponding to the zoom level, and renders only those entities of the layer that intersect the current viewport. The result is that, regardless of the graph size, the number of entities rendered at each view does not exceed a predefined threshold, yet all graph elements can be explored by the standard zoom and pan operations. GraphMaps preprocesses a graph in such a way that during browsing, the geometry of the entities is stable, and the viewer is responsive. Our case studies indicate that GraphMaps is useful in gaining an overview of a large graph, and also in exploring a graph on a finer level of detail.

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Generalizing Geometric Graphs

Cited by 6 publications

References 29 publications

A New Approach to GraphMaps, a System Browsing Large Graphs as Interactive Maps

A New Approach to GraphMaps, a System Browsing Large Graphs as Interactive Maps

Exploring Complex Drawings via Edge Stratification

GraphMaps: Browsing Large Graphs as Interactive Maps

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