Implementation of an interactive visualization tool for analyzing dynamic hierarchies

Many real world examples can be found that deal with hierarchical data. Software systems typically consist of packages, directories, subdirectories, files, classes, and functions. Phylogenetic trees structure biological species into a hierarchical organization. Visualizing such static hierarchical data has been in focus of Information Visualization for many years. Visually encoding and understanding of evolving hierarchies still remains a challenging task. Since hierarchies may grow huge and may evolve over a long time producing many time steps, we make use of a side-by-side and aligned representation of Indented Pixel Tree Plots. To achieve a mental map preserving overview-based diagram we show the dynamics of a hierarchy by a static representation and illustrate the changes between subsequent hierarchies by special links. Interactive features make the data manipulable and navigable in all dimensions

Overlap-free Drawing of Generalized Pythagoras Trees for Hierarchy Visualization

Generalized Pythagoras trees were developed for visualizing hierarchical data, producing organic, fractal-like representations. However, the drawback of the original layout algorithm is visual overlap of tree branches. To avoid such overlap, we introduce an adapted drawing algorithm using ellipses instead of circles to recursively place tree nodes representing the subhierarchies. Our technique is demonstrated by resolving overlap in diverse real-world and generated datasets, while comparing the results to the original approach

D.: Indented pixel tree plots

Abstract. We introduce Indented Pixel Tree Plots (IPTPs): a novel pixel-based visualization technique for depicting large hierarchies. It is inspired by the visual metaphor of indented outlines, omnipresent in graphical file browsers and pretty printing of source code. Inner vertices are represented as vertically arranged lines and leaf groups as horizontally arranged lines. A recursive layout algorithm places parent nodes to the left side of their underlying tree structure and leaves of each subtree grouped to the rightmost position. Edges are represented only implicitly by the vertically and horizontally aligned structure of the plot, leading to a sparse and redundant-free visual representation. We conducted a user study with 30 subjects in that we compared IPTPs and node-link diagrams as a within-subjects variable. The study indicates that working with IPTPs can be learned in less than 10 minutes. Moreover, IPTPs are as effective as node-link diagrams for accuracy and completion time for three typical tasks; participants generally preferred IPTPs. We demonstrate the usefulness of IPTPs by understanding hierarchical features of huge trees such as the NCBI taxonomy with more than 300,000 nodes.