PaisleyTrees: A Size-Invariant Tree Visualization (original) (raw)

Symmetry and Node Focused Visualization of Large Trees

In this paper, we take a different approach to visualizing very large trees. To facilitate presentation and exploration of massive hierarchical datasets such as linguistic and genealogical hierarchies, our approach considers drawing layouts of tree-cuts as a function of a node-of-interest or NOI, and uses interaction to support rapid access to the entire tree. Instead of emphasizing overall tree structure, our layout is designed to make the most space available for the node-of-interest and its immediate ancestors and descendants. Inspired from Persian floral patterns, we describe the development of ShamsehTree and PaisleyTree, showing how the use of symmetry can provide new structures for tree layouts.

Browsing Zoomable Treemaps: Structure-Aware Multi-Scale Navigation Techniques

IEEE Transactions on Visualization and Computer Graphics, 2000

Treemaps provide an interesting solution for representing hierarchical data. However, most studies have mainly focused on layout algorithms and paid limited attention to the interaction with treemaps. This makes it difficult to explore large data sets and to get access to details, especially to those related to the leaves of the trees. We propose the notion of zoomable treemaps (ZTMs), an hybridization between treemaps and zoomable user interfaces that facilitates the navigation in large hierarchical data sets. By providing a consistent set of interaction techniques, ZTMs make it possible for users to browse through very large data sets (e.g., 700,000 nodes dispatched amongst 13 levels). These techniques use the structure of the displayed data to guide the interaction and provide a way to improve interactive navigation in treemaps.

Enabling effective tree exploration using visual cues

Journal of Visual Languages & Computing, 2018

This article presents a new interactive visualization for exploring large hierarchical structures by providing visual cues on a node link tree visualization. Our technique provides topological previews of hidden substructures with three types of visual cues including simple cues, tree cues and treemap cues. We demonstrate the visual cues on Degree-of-Interest Tree (DOITree) due to its familiar mapping, its capability of providing multiple focused nodes, and its dynamic rescaling of substructures to fit the available space. We conducted a usability study with 28 participants that measured completion time and accuracy across five different topology search tasks. The simple cues had the fastest completion time across three of the node identification tasks. The treemap cues had the highest rate of correct answers on four of the five tasks, although only reaching statistical significance for two of these. As predicted, user ratings demonstrated a preference for the easy to understand tree cues followed by the simple cue, despite this not consistently reflected in performance results.

Tree visualization with Tree-maps: A 2-d space-filling approach

ACM Transactions on Graphics, 1991

The traditional approach to representing tree structures is as a rooted, directed graph with the root node at the top of the page and children nodes below the parent node with lines connecting them ( ). Knuth (1968, p. 305-313) has a long discussion about this standard representation, especially why the root is at the top and he offers several alternatives including brief mention of a space-filling approach. However, the remainder of his presentation and most other discussions of trees focus on various node and edge representations. By contrast, this paper deals with a two-dimensional (2-d) space-filling approach in which each node is a rectangle whose area is proportional to some attribute such as node size.

Tree visualization with tree-maps: 2-d space-filling approach

1992

Introduction. The traditional approach to representing tree structures is as a rooted, directed graph with the root node at the top of the page and children nodes below the parent node with lines connecting them (Figure 1). Knuth[21 has a long discussion about this standard representation, especially why the root is at the top, and he offers several alternatives including brief mention of a space-filling approach.

Using Visual Cues on DOITree for Visualizing Large Hierarchical Data

2014 18th International Conference on Information Visualisation, 2014

This paper extends a previous work on node link tree visualization and interaction by providing visual clues on hidden structures. We adopt the effectiveness of DOITree, a multi-focal tree layout algorithm, for exploring large hierarchical structures. The advantages of visualization are its most familiar mapping for users, its capability on providing multiple focused nodes, and its dynamic rescaling of substructures to fit the available space. By providing various methods of topological previews of substructure including simple icon view, tree view and treemap view, we provide better understanding the topology of hidden branches.

Improvements of Space-Optimized Tree for Visualizing and Manipulating Very Large Hierarchies

2002

This paper describes some improvements over the original Space-Optimized Tree technique for the visualization and manipulation of very large hierarchies. The new system uses an improved algorithm to calculate geometrical layouts and it also provides better navigation capability. We introduce our new layout algorithm that can make more consistence of the display than the original layout technique made. We also combine DualView (a new focus+context technique) with the current modified semantic zooming in order to interactively navigate through the large and very large hierarchies.

Tree-maps: A space-filling approach to the visualization of hierarchical information structures

1991

Abstract A method for visualizing hierarchically structured information is described. The tree-map visualization technique makes 100% use of the available display space, mapping the full hierarchy onto a rectangular region in a space-filling manner. This efficient use of space allows very large hierarchies to be displayed in their entirety and facilitates the presentation of semantic information. Tree-maps can depict both the structure and content of the hierarchy.