Network visualization allows a quick glance at how nodes (or actors) are connected by edges (or ties). A conventional network diagram of "contact tree" maps out a root and branches that represent the structure of nodes and edges, often without further specifying leaves or fruits that would have grown from small branches. By furnishing such a network structure with leaves and fruits, we reveal details about "contacts" in our ContactTrees that underline ties and relationships. Our elegant design employs a bottom-up approach that resembles a recent attempt to understand subjective well-being by means of a series of emotions. Such a bottom-up approach to social-network studies decomposes each tie into a series of interactions or contacts, which help deepen our understanding of the complexity embedded in a network structure. Unlike previous network visualizations, ContactTrees can highlight how relationships form and change based upon interactions among actors, and how relationships and networks vary by contact attributes. Based on a botanical tree metaphor, the design is easy to construct and the resulting tree-like visualization can display many properties at both tie and contact levels, a key ingredient missing from conventional techniques of network visualization. We first demonstrate ContactTrees using a dataset consisting of three waves of 3-month contact diaries over the 2004-2012 period, then compare ContactTrees with alternative tools and discuss how this tool can be applied to other types of datasets.
This technique is inspiring but not sufficient for our purpose. First, not only do we focus on how network members are directly connected to a focal person, we also aim to map various properties of these members. Second, in addition to such relationships and properties, we want to further distinguish the attributes of social interactions between each network member and the focal person, contact by contact. There are three main approaches for the visualization of trees. According to the paradigm of node-link diagrams, persons are represented by small shapes and relations by lines. A good introduction to the techniques is given by two books on graph drawing @cite_25 @cite_0 and the website http: treevis.net @cite_43 . Persons can also be represented by areas and relations by the positioning of these areas. This is the case of @cite_47 , @cite_23 and @cite_48 . The third approach is to visualize tree elements as nested areas. Two kind of methods have been proposed to create such maps: (1) dividing the plan recursively (a detailed overview by Ben Shneiderman, and updated by Catherine Plaisant, can be found at @cite_8 ) (2) positioning leaves along space-filing curves @cite_18 .
@cite_18 @cite_8 @cite_48 @cite_0 @cite_43 @cite_23 @cite_47 @cite_25
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The emergence of very large hierarchies that result from the increase in available data raises many problems of visualization and navigation. On data sets of such scale, classical graph drawing methods do not take advantage of certain human cognitive skills such as shape recognition. These cognitive skills could make it easier to remember the global structure of the data. In this paper, we propose a method that is based on the use of nested irregular shapes. We name it GosperMap as we rely on the use of a Gosper Curve to generate these shapes. By employing human perception mechanisms that were developed by handling, for example, cartographic maps, this technique facilitates the visualization and navigation of a hierarchy. An algorithm has been designed to preserve region containment according to the hierarchy and to set the leaves' sizes proportionally to a property, in such a way that the size of nonleaf regions corresponds to the sum of their children's sizes. Moreover, the input ordering of the hierarchy's nodes is preserved, i.e., the areas that represent two consecutive children of a node in the hierarchy are adjacent to one another. This property is especially useful because it guarantees some stability in our algorithm. We illustrate our technique by providing visualization examples of the repartition of tax money in the US over time. Furthermore, we validate the use of the GosperMap in a professional documentation context and show the stability and ease of memorization for this type of map. During 1990, in response to the common problem of a filled hard disk, I became obsessed with the idea of producing a compact visualization of directory tree structures. Since the 80 Megabyte hard disk in the HCIL was shared by 14 users it was difficult to determine how and where space was used. Finding large files that could be deleted, or even determining which users consumed the largest shares of disk space were difficult tasks. Radial, space-filling visualizations can be useful for depicting information hierarchies, but they suffer from one major problem. As the hierarchy grows in size, many items become small, peripheral slices that are difficult to distinguish. We have developed three visualization interaction techniques that provide flexible browsing of the display. The techniques allow viewers to examine the small items in detail while providing context within the entire information hierarchy. Additionally, smooth transitions between views help users maintain orientation within the complete information space. This paper presents work in progress on a new technique for visu- alising and manipulating large hierarchies. The information slices approach compactly visualises hierarchical structures using a series of semi-circular discs. The technique is described in the context of our early experience with a prototype file system visualiser based on information slices. Over the last few years, the emerging field of information visuali- sation has resulted in a numerous techniques for helping visualise and make sense of large information spaces (10). Among these are several techniques for visualising and interacting with large hierar- chies which go beyond the traditional approach taken in 2d scrolling browsers such as the Windows Explorer. Treemaps (6, 9) are space-filling visualisations of hierarchies based on successive horizontal and vertical subdivision of screen rectangles. The area of each rectangle is proportional to some at- tribute of the underlying hierarchy such as the (total) size of each subtree. Xdu (4) is a utility for the X window system which displays a graphical disk usage for Unix file systems. Rectangles are stacked from left to right as the directory tree is descended. The current di- rectory is represented by the leftmost rectangle, which is the entire height of the window. Subdirectories are represented by neighbour- ing rectangles in the next column, whose height are proportional to the size of each subdirectory. The hyperbolic browser (7) uses a focus and context technique based on hyperbolic geometry. A hierarchy is laid out uniformly on the hyperbolic plane and then mapped to the unit disc for display on screen. Nodes in the centre of the disc are largest and nodes are assigned progressively less space towards the perimeter of the disc. Cheops (3) is based on multiple re-use of overlaid triangles in the display. Working top-down, the selection of a node (triangle) at a particular level designates that node's children are to be represented Abstract An icicle plot is a method for presenting a hierarchical clustering. Compared with other methods of presentation, it is far easier in an icicle plot to read off which objects belong to which clusters, and which objects join or drop out from a cluster as we move up and down the levels of the hierarchy, though these benefits only appear when enough objects are being clustered. Icicle plots are described, and their benefits are illustrated using a clustering of 48 objects. From the Publisher: This book is designed to describe fundamental algorithmic techniques for constructing drawings of graphs. Suitable as a book or reference manual, its chapters offer an accurate, accessible reflection of the rapidly expanding field of graph drawing.