Understanding constellations in large data collections has become a common task. One obstacle a user has to overcome is the internal complexity of these repositories. For example, extracting connected data from a normalized relational database requires knowledge of the table structure which might not be available for the casual user. In this paper we present a visualization framework which presents the collection as a set of entities and relations (on the data level). Using rating functions, we divide large relation networks into small graphs which resemble ego-centered networks. These graphs are connected so the user can browse from one to another. To further assist the user, we present two views which embed information on the evolution of the relations into the graphs. Each view emphasizes another aspect of temporal development. The framework can be adapted to any repository by a flexible data interface and a graph configuration file. We present some first web-based applications including a visualization of the DBLP data set. We use the DBLP visualization to evaluate our approach.
Aggregated approaches show the temporal data in a single drawing. LifeLines @cite_10 visualizes a person's disease pattern. For each condition there is a timeline, i.e., a horizontal bar along a time axis. Coloration and thickness of these bars change to show the status of the condition at different times. TimeRadarTrees @cite_11 uses a radial drawing to show how several entities are related with each other. Unlike our approach, there is no ego and all relations between the visible nodes are displayed. Instead of node-link, it uses colored segments which fill a circle with multiple layers. The approach is limited to small graphs but supports hierarchical nesting to compensate this. Segments at the perimeter represent recent events while those near the center represent old influences. The intensity view is similar to this drawing but has a much lower information density. ConfSearch @cite_2 searches DBLP for relations between conferences, authors and keywords. The related entities of an ego are presented as a rated list with additional information. ConfSearch does not show the evolution of relations, but we adopted some of the rating functions used for the examples in Section .
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Compound digraphs are a widely used model in computer science. In many application domains these models evolve over time. Only few approaches to visualize such dynamic compound digraphs exist and mostly use animation to show the dynamics. In this paper we present a new visualization tool called TimeArcTrees that visualizes weighted, dynamic compound digraphs by drawing a sequence of node-link diagrams in a single view. Compactness is achieved by aligning the nodes of a graph vertically. Edge crossings are reduced by drawing upward and downward edges separately as colored arcs. Horizontal alignment of the instances of the same node in different graphs facilitates comparison of the graphs in the sequence. Many interaction techniques allow to explore the given graphs. Smooth animation supports the user to better track the transitions between views and to preserve his or her mental map. We illustrate the usefulness of the tool by looking at the particular problem of how shortest paths evolve over time. To this end, we applied the system to an evolving graph representing the German Autobahn and its traffic jams. The evolution of dependencies in information hierarchies can be modeled by sequences of compound digraphs with edge weights. In this paper we present a novel approach to visualize such sequences of graphs. It uses radial tree layout to draw the hierarchy, and circle sectors to represent the temporal change of edges in the digraphs. We have developed several interaction techniques that allow the users to explore the structural and temporal data. Smooth animations help them to track the transitions between views. The usefulness of the approach is illustrated by examples from very different application domains. We present a novel dynamic graph visualization technique based on node-link diagrams. The graphs are drawn side-byside from left to right as a sequence of narrow stripes that are placed perpendicular to the horizontal time line. The hierarchically organized vertices of the graphs are arranged on vertical, parallel lines that bound the stripes; directed edges connect these vertices from left to right. To address massive overplotting of edges in huge graphs, we employ a splatting approach that transforms the edges to a pixel-based scalar field. This field represents the edge densities in a scalable way and is depicted by non-linear color mapping. The visualization method is complemented by interaction techniques that support data exploration by aggregation, filtering, brushing, and selective data zooming. Furthermore, we formalize graph patterns so that they can be interactively highlighted on demand. A case study on software releases explores the evolution of call graphs extracted from the JUnit open source software project. In a second application, we demonstrate the scalability of our approach by applying it to a bibliography dataset containing more than 1.5 million paper titles from 60 years of research history producing a vast amount of relations between title words. University of TrierKeywords: Graph visualization, node-link diagrams, radial layout, splattingAbstract: We describe and discuss a novel radial version of a scalable dynamic graph visualization. The radial layoutencodes dynamic directed graphs on narrow rings of a circle. The temporal evolution of the graph is mapped torings that grow outward from the center of the circle. Graph vertices are placed equidistantly at the borderlinesof each ring. Graph edges are displayed as curved lines starting from a source on the inner borderline of thering and pointing to a target on the outer borderline. To better perceive link directions and structures of largedatasets, visual clutter is reduced by exploiting an edge splatting approach that generates density ﬁelds of thedisplayed edges. The radial layout emphasizes newer graphs, displayed in the larger, outer parts of the circle.As a beneﬁt, edge lengths are reduced in comparison to the non-radial visualization. Moreover, the radiallayout guarantees the symmetry of the visualization under shifting of vertices. We illustrate the usefulness ofthe diagrams by applying them to call graph data of the open source software project Cobertura.