1 Airlines, Migrations, and Air Traffic
Origin Notes: Data collected from the Edge-Path bundling paper by Markus Wallinger et al. They cite the Airlines dataset to Force Directed Edge Bundling for Graph Visualization and the migrations dataset to Geometry-Based Edge Clustering for Graph Visualization. graph features handled: Bundled edges (generated), Directed edges, Generic, Spatial Graph features in papers: generic,spatial,spatial,clusters (generated),dynamic,spatial,bundled edges (generated),generic,bundled edges (generated),spatial,dynamic,dynamic (discrete),bundled edges (generated),directed edges,spatial Origin Paper: Force-Directed Edge Bundling for Graph Visualization (https://www.notion.so/Force-Directed-Edge-Bundling-for-Graph-Visualization-597d0c38c51e433090a7706cdc9bd6a3?pvs=21), Geometry-Based Edge Clustering for Graph Visualization (https://www.notion.so/Geometry-Based-Edge-Clustering-for-Graph-Visualization-72e7c5d193e34645a3cbca78df6fd1c8?pvs=21), Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach (https://www.notion.so/Edge-Path-Bundling-A-Less-Ambiguous-Edge-Bundling-Approach-be7daf7cd0ce4a73b1ad00bb25af472c?pvs=21) Originally found at: https://github.com/mwallinger-tu/edge-path-bundling/tree/master/data Size: 235-1702 nodes, 2101-16494 edges Number of Graphs: 3 format: JSON file but with spcific attributes for their tool so needs to be parsed Appeared in years: 2011,2009,2016,2008,2017,2020,2022,2023 Type of Collection: Aggregate collection is it stored properly?: No must be analyzed: No In repo?: Yes Related to Literature - Algorithm (1) (Dataset tag relations): Force-directed edge bundling for graph visualization (https://www.notion.so/Force-directed-edge-bundling-for-graph-visualization-09ec16bfe40d4fbea880bfc4e640bbfa?pvs=21), MLSEB: Edge Bundling Using Moving Least Squares Approximation (https://www.notion.so/MLSEB-Edge-Bundling-Using-Moving-Least-Squares-Approximation-474c60d6caff41a3a09b5ba2f1f513d8?pvs=21), HOTVis: Higher-Order Time-Aware Visualisation of Dynamic Graphs (https://www.notion.so/HOTVis-Higher-Order-Time-Aware-Visualisation-of-Dynamic-Graphs-4ce353bf13094484988b5f8bb306c8d8?pvs=21), MobilityGraphs: Visual Analysis of Mass Mobility Dynamics via Spatio-Temporal Graphs and Clustering (https://www.notion.so/MobilityGraphs-Visual-Analysis-of-Mass-Mobility-Dynamics-via-Spatio-Temporal-Graphs-and-Clustering-69e89e0d31134f8997cdaaa266e4ba9c?pvs=21), Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach (https://www.notion.so/Edge-Path-Bundling-A-Less-Ambiguous-Edge-Bundling-Approach-932f56be1ec24c50a2c3fc65a37ed172?pvs=21), Geometry-Based Edge Clustering for Graph Visualization (https://www.notion.so/Geometry-Based-Edge-Clustering-for-Graph-Visualization-c3e8767d7784426f815b386900c6cee9?pvs=21), Skeleton-Based Edge Bundling for Graph Visualization (https://www.notion.so/Skeleton-Based-Edge-Bundling-for-Graph-Visualization-f62005dde2124553a06f4f0883976ca9?pvs=21) cleaned format?: Yes duplicate?: No link works?: Yes Added in paper: No OSF link json: https://files.osf.io/v1/resources/j7ucv/providers/osfstorage/64d90e774cf7480ef0055631 Origin paper plaintext: Force-Directed Edge Bundling for Graph Visualization, Geometry-Based Edge Clustering for Graph Visualization, Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach Page id: 45ffa6caedd141b082e163d7da6eb895 unavailable/skip: No Cleaned ALL data: No OSF link gexf: https://files.osf.io/v1/resources/j7ucv/providers/osfstorage/64d9490a1101aa0dcf6a0ba5 OSF link gml: https://files.osf.io/v1/resources/j7ucv/providers/osfstorage/64d96d8c0c2b4d0f64386243 OSF link graphml: https://files.osf.io/v1/resources/j7ucv/providers/osfstorage/64d971241101aa0e9f6a0c0b first look: No sparkline data: {‘min’: 235, ‘max’: 1702, ‘step_size’: 1500, ‘num_bins’: 2, ‘bins’: [0, 1500], ‘num_nodes’: [1, 2]} Related to Literature - Algorithm (Dataset tag relations) 1: Skeleton-Based Edge Bundling for Graph Visualization (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/Skeleton-Based%20Edge%20Bundling%20for%20Graph%20Visualizati%206dd78ad2473945c99d670dea9546af1c.md), Force-directed edge bundling for graph visualization (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/Force-directed%20edge%20bundling%20for%20graph%20visualizati%201a6dc388a0f4443ca2d3693f8bff3f74.md), MobilityGraphs: Visual Analysis of Mass Mobility Dynamics via Spatio-Temporal Graphs and Clustering (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/MobilityGraphs%20Visual%20Analysis%20of%20Mass%20Mobility%20Dy%2003cbcaf73d9b4c0784e8e44b38185eb6.md), Geometry-Based Edge Clustering for Graph Visualization (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/Geometry-Based%20Edge%20Clustering%20for%20Graph%20Visualiza%204266d74d6ae1420a970d2b1a74a38fc7.md), MLSEB: Edge Bundling Using Moving Least Squares Approximation (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/MLSEB%20Edge%20Bundling%20Using%20Moving%20Least%20Squares%20App%20bf3edb74a4cd4476838fdcc3d531f9b5.md), HOTVis: Higher-Order Time-Aware Visualisation of Dynamic Graphs (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/HOTVis%20Higher-Order%20Time-Aware%20Visualisation%20of%20Dy%20bd698d90a24a4b8e9527007489d139b5.md), Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/Edge-Path%20Bundling%20A%20Less%20Ambiguous%20Edge%20Bundling%20%20fcfa5882e692481298cbee906e005c30.md), Interactive Structure-aware Blending of Diverse Edge Bundling Visualizations (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/Interactive%20Structure-aware%20Blending%20of%20Diverse%20Ed%204fbfba72a5b046f8baf7211508790373.md), Faster Edge-Path Bundling through Graph Spanners (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/Faster%20Edge-Path%20Bundling%20through%20Graph%20Spanners%2064dc9f75adc942ffb7dd7259a8357cf8.md)
2 Body
Statistics
Descriptions from Literature
From “Skeleton-Based Edge Bundling for Graph Visualization”:
Figure 7 illustrates the SBEB and compares it with several existing bundling methods. Note that in all images here generated with our method, we used simple additive edge blending only, as our focus here is the layout, not the rendering. Images (a,b) show an air traffic graph (nodes are city locations, edges are interconnecting flights)… Images (e-h) show the US migrations graph bundled with the WR, GBEB, FDEB, and our method (SBEB) respectively. Overall, SBEB produces stronger bundling, due to the many iterations I = 10 being used), and emphasizes the structure of connections between groups of close cities (due to the skeleton layout cues). If less bundling is desired, fewer iterations can be used (Fig. 4). Adjusting the postprocessing smoothing and relaxation parameters, SBEB can create bundling styles similar to either GBEB (higher bundle curvatures, more emphasis on the graph structure) or FDEB (smoother bundles). Finally, images (i,j) show the US airlines graph bundled with the FDEB and SBEB respectively. SBEB generates stronger bundling (more overdraw) but arguably less clutter. Note also that SBEB generates treelike bundle structures which is useful when the exploration task at hand has an inherent (local) hierarchical nature, e.g. see how traffic connections merge into and/or split from main traffic routes.
Example Figures
From “Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach”:
Fig. 1. Edge bundling of the migrations dataset. (a) Straight line drawing. (b) Force-directed edge bundling aggregates edges well, but overaggregates at the centre of the drawing making it difficult to see patterns in the east-west flow (red bundle). (c) Cubu has a similar drawback at the centre of the map to a lesser degree. (d) Winding roads divides this structure into several smaller flows, but they may not be necessarily related to graph structure. (e) Edge-path bundling is able to distinguish between several flows that reflect paths in the underlying graph. (f) When edge direction is considered, the algorithm is able to further subdivide these flows based on direction.
Fig. 8. Airlines (undirected). (a) Input drawing. (b) Force-directed bundling is able to cluster edges into the major flows, but some overaggregation prevents details from being visualised. (c) Cubu provides a good bundling, but also has overaggregation. (c) Confluent drawings can be imposed on the layout, but as the approach cannot layout the graph bicliques can be distantly located, resulting in suboptimal performance. (e) Winding roads divides the flows into many streams, but these streams can be unfaithful to graph structure. (f) Edge-path bundling aggregates edges using weighted paths. The four prominent bundle intersections on the east coast correspond to major airports: Atlanta, Detroit, Minneapolis, and Dallas.
Fig. 10. Results of four algorithms on the air traffic network. (a) Force-directed bundling is able to recover the major trajectories but does not strongly bundle the network. (b) Cubu strongly bundles the main flows of airtraffic, but can suffer from overaggregation. (c) Winding roads divides the traffic into many smaller bundles, but this may not be reflective of underlying graph structure. (d) With edge-path bundling, each bundle necessarily reflects a path in the network. There are separate flows across the atlantic and asia that correspond to paths through the network.
From “Skeleton-Based Edge Bundling for Graph Visualization”:
== STOP RENDERING ==
gd contest: http://www.research.att.com/conf/gd96/contest.html
look here: https://github.com/mwallinger-tu/edge-path-bundling/tree/master/data from Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach