text: 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.
  @cite_2: Recent models have introduced the notion of dimensions and hierarchies in social networks. These models motivate the mining of small world graphs under a new perspective. We exemplary base our work on a conference graph, which is constructed from the DBLP publication records. We show that this graph indeed exhibits a layered structure as the models suggest. We then introduce a subtraction approach that allows to segregate layers. Using this technique we separate the conference graph into a thematic and a quality layer. As concrete applications of the discussed methods we present a novel rating method as well as a conference search tool that bases on our graph and its layer separation.
  @cite_10: LifeLines provide a general visualization environment for personal histories that can be applied to medical and court records, professional histories and other types of biographical data. A one screen overview shows multiple facets of the records. Aspects, for example medical conditions or legal cases, are displayed as individual time lines, while icons indicate discrete events, such as physician consultations or legal reviews. Line color and thickness illustrate relationships or significance, rescaling tools and filters allow users to focus on part of the information. LifeLines reduce the chances of missing information, facilitate spotting anomalies and trends, streamline access to details, while remaining tailorable and easily transferable between applications. The paper describes the use of LifeLines for youth records of the Maryland Department of Juvenile Justice and also for medical records. User's feedback was collected using a Visual Basic prototype for the youth record. Techniques to deal with complex records are reviewed and issues of a standard personal record format are discussed.
  @cite_11: 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.
summary: 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 .