Abstract—A compound graph is a frequently encountered type of data set. Relations are given between items, and a hierarchy is defined on the items as well. We present a new method for visualizing such compound graphs. Our approach is based on visually bundling the adjacency edges, i.e., non-hierarchical edges, together. We realize this as follows. We assume that the hierarchy is shown via a standard tree visualization method. Next, we bend each adjacency edge, modeled as a B-spline curve, toward the polyline defined by the path via the inclusion edges from one node to another. This hierarchical bundling reduces visual clutter and also visualizes implicit adjacency edges between parent nodes that are the result of explicit adjacency edges between their respective child nodes. Furthermore, hierarchical edge bundling is a generic method which can be used in conjunction with existing tree visualization techniques. We illustrate our technique by providing example visualizations and discuss the results based on an informal evaluation provided by potential users of such visualizations.

The need to visualize large social networks is growing as hardware capabilities make analyzing large networks feasible and many new data sets become available. Unfortunately, the visualizations in existing systems do not satisfactorily resolve the basic dilemma of being readable both for the global structure of the network and also for detailed analysis of local communities. To address this problem, we present NodeTrix, a hybrid representation for networks that combines the advantages of two traditional representations: node-link diagrams are used to show the global structure of a network, while arbitrary portions of the network can be shown as adjacency matrices to better support the analysis of communities. A key contribution is a set of interaction techniques. These allow analysts to create a NodeTrix visualization by dragging selections to and from node-link and matrix forms, and to flexibly manipulate the NodeTrix representation to explore the dataset and create meaningful summary visualizations of their findings. Finally, we present a case study applying NodeTrix to the analysis of the InfoVis 2004 coauthorship dataset to illustrate the capabilities of NodeTrix as both an exploration tool and an effective means of communicating results.

rolled up onto two categorical dimensions This paper introduces PivotGraph, a software tool that uses a new technique for visualizing and analyzing graph structures. The technique is designed specifically for graphs that are “multivariate, ” i.e., where each node is associated with several attributes. Unlike visualizations which emphasize global graph topology, PivotGraph uses a simple grid-based approach to focus on the relationship between node attributes and connections. The interaction technique is derived from an analogy with methods seen in spreadsheet pivot tables and in online analytical processing (OLAP). Finally, several examples are presented in which PivotGraph was applied to real-world data sets.

Abstract — We present VisLink, a method by which visualizations and the relationships between them can be interactively explored. VisLink readily generalizes to support multiple visualizations, empowers inter-representational queries, and enables the reuse of the spatial variables, thus supporting efficient information encoding and providing for powerful visualization bridging. Our approach uses multiple 2D layouts, drawing each one in its own plane. These planes can then be placed and re-positioned in 3D space: side by side, in parallel, or in chosen placements that provide favoured views. Relationships, connections, and patterns between visualizations can be revealed and explored using a variety of interaction techniques including spreading activation and search filters. Index Terms—Graph visualization, node-link diagrams, structural comparison, hierarchies, 3D visualization, edge aggregation. 1

We investigate the use of elastic hierarchies for representing trees, where a single graphical depiction uses a hybrid mixture, or "interleaving", of more basic forms at different nodes of the tree. In particular, we explore combinations of node-link and Treemap forms, to combine the space-efficiency of Treemaps with the structural clarity of node-link diagrams. A taxonomy is developed to characterize the design space of such hybrid combinations. A software prototype is described, which we used to explore various techniques for visualizing, browsing and interacting with elastic hierarchies, such as side-by-side overview and detail views, highlighting and rubber banding across views, visualization of multiple foci, and smooth animations across transitions. The paper concludes with a discussion of the characteristics of elastic hierarchies and suggestions for research on their properties and uses.

Abstract—While many data sets contain multiple relationships, depicting more than one data relationship within a single visualization is challenging. We introduce Bubble Sets as a visualization technique for data that has both a primary data relation with a semantically significant spatial organization and a significant set membership relation in which members of the same set are not necessarily adjacent in the primary layout. In order to maintain the spatial rights of the primary data relation, we avoid layout adjustment techniques that improve set cluster continuity and density. Instead, we use a continuous, possibly concave, isocontour to delineate set membership, without disrupting the primary layout. Optimizations minimize cluster overlap and provide for calculation of the isocontours at interactive speeds. Case studies show how this technique can be used to indicate multiple sets on a variety of common visualizations. Index Terms—clustering, spatial layout, graph visualization, tree visualization. 1

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. Categories and Subject Descriptors (according to ACM CCS): E.1 [Data Structures]: Graphs and Networks 1.

Graphs are often visualized using node-link representations: vertices are depicted as dots, edges are depicted as (poly)lines connecting two vertices. A directed edge running from vertex A to B is generally visualized using an arrow representation: a (poly)line with a triangular arrowhead at vertex B. Although this representation is intuitive, it is not guaranteed that a user is able to determine edge direction as quickly and unambiguously as possible; alternative representations that exhibit less occlusion and visual clutter might be better suited. To investigate this, we developed five additional directed-edge representations using combinations of shape and color. We performed a user study in which subjects performed different tasks on a collection of graphs using these representations and combinations thereof to investigate which representation is best in terms of speed and accuracy. We present our initial hypotheses, the outcome of the user studies, and recommendations regarding directed-edge visualization.

apport de recherche ISSN 0249-6399 ISRN INRIA/RR--6183--FR+ENG

In many applications transactions between the elements of an information hierarchy occur over time. For example, the product offers of a department store can be organized into product groups and subgroups to form an information hierarchy. A market basket consisting of the products bought by a customer forms a transaction. Market baskets of one or more customers can be ordered by time into a sequence of transactions. Each item in a transaction is associated with a measure, for example, the amount paid for a product. In this paper we present a novel method for visualizing sequences of these kinds of transactions in information hierarchies. It uses a tree layout to draw the hierarchy and a timeline to represent progression of transactions in the hierarchy. We have developed several interaction techniques that allow the users to explore the data. Smooth animations help them to track the transitions between views. The usefulness of the approach is illustrated by examples from several very different application domains. There has been a lot of work on visualizing such hierarchies using node-link diagrams [12], radial [16], or space-filling techniques like Treemaps [7], Information Slices [1], or Sunburst [14]. In the application domains mentioned above, there are also relations between elements in the hierarchy. For example, employees are related if they communicate with each other, topics are related if they are covered in the daily newscast, files are related if they are changed simultaneously by the same person, or products are related if they are bought by the same customer at the same time. Through these relations the participating elements together form a transaction. So far, only few researchers have developed methods to visualize such transactions between elements of a hierarchy [10,