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anemone
using the process of organic information design to visualize the changing structure of a web site, juxtaposed with usage information



 
What does a web site’s structure look like? A site is made up of thousands of pages, all linked together in a tree-shaped structure. A ‘map’ of the structure can be drawn using illustration software, but the diagram quickly becomes tangled in anomalies because the site is not as hierarchical as would be expected. To further complicate matters, the contents of the site are continually changing. Web pages are added and removed daily, so by the time the map could be finished, it would already be inaccurate. How can these changes be represented visually?

How can a connection be made between the site’s usage statistics and that structure? How can the paths that visitors take through the site be expressed? A number next to each page could keep track of the total number of visitors, but because the traffic patterns are continually changing, it becomes clear that the totals aren’t as useful as hoped. How can the day to day and month to month changes in these numbers be expressed? How can the movement between pages be represented, making it apparent that some areas are more closely related than others?

Anemone is a project that uses the process of Organic Information Design to make this set of problems more approachable. Data from the Aesthetics and Computation Group’s web site was used as input in the examples shown here. Rules for growth can govern the creation of new branches of structure within the site. Atrophy rules decay unused areas, eventually removing them. Individual web pages can call attention to themselves as they are visited more rapidly than others. A set of rules governing movement can group related areas.


Figure 1 several steps showing growth of the web site’s structure

Individual branches grow based on input from the data. As the Preprocessor Engine reads the usage log, a reproduction rule causes branches to grow whenever parts of the site are visited for the first time. This avoids the problem of having to keep track of what pages are added to or removed from the site. Using the usage data to create an implicit model of structure is a common theme in Organic Information Design. To balance growth is the notion of ‘atrophy’. Branches associated with areas of the site that have not been visited will slowly wither away, causing them to visually thin out. Eventually the branches die, and are removed from the system.

A movement rule keeps the individual nodes within a set distance from their parent node. A second rule maintains a distance between nodes and their neighbors, so that branches overlap as little as possible. The composition is brought to life through the interactions of the growth and movement rules. The figure moves about the screen in a hyper, erratic fashion as it creates the initial parts of the visualization. After some time, this growth reaches an equilibrium and the pseudo-organism ‘settles’.

 
Figure 2 nodes attracting attention and declaring their importance through changes in thickness

Nodes at the tip of each branch represent a web pages. As seen in figure 2, each time a user visits a page, its node in the visualization becomes slightly thicker. Nodes for pages that are visited often become very thick relative to other nodes. This can happen rapidly, as nodes attempt to ‘call attention’ to themselves.

If several users visit a particular section of the site, that group of nodes will collectively thicken, drawing attention to the group. An interesting phenomenon can be watched as it propagates back through the site structure. For example, many people may visit the site from a link referring to it in the Yahoo directory (www.yahoo.com). This traffic can be watched while it propagates outward from the linked page.


Figure 3 progress of thickening in a group of related nodes

In addition, the appearance of the nodes self-regulate. If a particular page is frequently and consistently visited, its associated node in the visualization will thicken, but only up to a certain threshold. Not much additional information is learned therefore there is no need to allow the node to grow to enormous proportions. This homeostasis rule causes the node to settle to a certain size until changes in its use occur.

The Anemone experiment looks at how structural information can be juxtaposed with less structured usage patterns. Figure 4 is an image of Anemone with two layers. The top layer is the directory structure of the site (depicted with branches), determining a hierarchy for where individual web pages are located. The layer beneath represents the paths taken by users as they visit the site.


Figure 4 the two layers of Anemone, juxtaposing structured hierarchy with nonlinear usage

The paths can follow the directory structure, which is closely related to the link structure, as in the case of the web site being visualized here. The paths can also have disparate jumps to various areas of the site. Looking at the two layers together show interesting trends in the paths that large quantities of users take through the site. For instance, a large number of paths can be seen that connect the home page of Professor Maeda into other areas of the site. This is because many external links point to his page. In addition, a large number of visitors arrive from search engines having queried for his name.


Figure 5 user interaction, dragging nodes with the mouse

User interaction with this visualization is important. The viewer can click a node to discover which web page it represents (figure 5). They can also move nodes around as a way to peek inside the data set and take a closer look at what’s happening. Nodes can be dragged about the screen, pinned down, and watched in relation to other parts of the structure.




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